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LinkedIN -Jerome Vittoz - CRM 12 - Thesis MA Final

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LinkedIN -Jerome Vittoz - CRM 12 - Thesis MA Final

  1. 1. Marketing Automation Strategies for CRM leadership Marketing efficiency and revenue generation, analysis of methods that works Jerome Vittoz, Buehlstrasse 47, 8055 Zürich Masterarbeit am Institut für Marketing Management, Zürcher Hochschule für Angewandte Wissenshaften Master Thesis Director: Dr. Roger Seiler Zürcher Hochschule für Angewandte Wissenshaften Supporting Lecturer: Prof Dr. Frank Hannich Zürcher Hochschule für Angewandte Wissenshaften
  2. 2. 2 1 Introduction 1.1 Preface A special thanks to Petra Staudenmeier, former Head of International Marketing at Lindt & Srpüngli for her support and in making my attendance of this Master program possible. Thanks to Uwe Sommer, Lindt & Sprüngli group Vice President and member of Group Management for his confidence and encouragement in developing digital marketing at Lindt & Sprüngli. I do thank Dr. Roger Seiler and Prof Dr. Frank Hannich – Zürich University of Applied Science for their guidance along the redaction of this paper.
  3. 3. 3 2 Management Summary Name of the thesis: Marketing Automation Strategies for CRM leadership: Marketing efficiency and revenue generation, analysis of methods that works. Objectives: The objectives of the thesis is to help the reader understand how Marketing Automation strategies lead companies to CRM leadership and most importantly increase marketing efficiency and revenue generation. Lead Research questions: What are the required means, skills, tools and processes for successful Marketing Automation, leading to marketing efficiency and more revenue generation? Methods and procedure: The desk research has built the base for the qualitative content research study. Then the study was based on the interviews transcription of twelve Marketing Automation experts representing companies of different sizes, regions business models. The interviews have been interpreted using the technique of qualitative content analysis exposed in chapter 6.1.2. Finally, we have discussed the our findings and conclusions in the chapter 6.3 and 6.4. Major findings: Marketing Automation should be considered as fundamental component of any customer centric strategy. It is most suitable for companies with large volume of customer interactions across complex digital customer journeys and to improve marketing efficiency processes. Root cause: Marketing Automation can be implemented and used for many different reasons and not only for marketing efficiency or revenue generation. Managing an important volume of customer interactions is the primarily reasons for implementing it. However, it can also bring advantages in data quality management, in developing a customer centric strategy, sorting out organizational issues especially coordinating marketing and sales efforts, increasing customer satisfaction, develop customer personalization and customer scoring. What are the methods that works? System architecture: The ideal marketing solution does not exist. Nevertheless, conceptually the integration should consist of a data management layer, enriched with
  4. 4. 4 another marketing orchestration layer and finally a layer for customer interfaces such as CMS, e-commerce or any advertising medium. The whole works in a closed-loop in order to constantly enrich customer ID profiles and improve profiling by using scoring methods. Data Management: Data quality is the most important element of a solid marketing automation strategy. Methods such as data normalization, progressive profiling should be carefully implemented. Marketing Automation in combination with a data management platform, a clear customer referential with a unique record ID is the required conditions to secure elementary data quality. Organization & Processes: Successful Marketing Automation’s manager’s benefits from the support of their management with clearly defined business question and know their success factors. The implementation of Marketing Automation is an iterative and multidisciplinary project between marketing, sales, IT and sometimes with the support of a consulting agency. The initial process of creating Marketing Automation flows should be using the customer journey mapping method. Best practices Marketing Automation: Most successful marketing automation rules are the ones that answer business questions. In our research, most often cited Marketing Automation programs were: the look alike modelling program, the welcome nurturing series, the first order push, the abandoned cart, the drive to store, the search triggered campaign, the lapsing prevention program, the happy customers programs (see chapter 6.2.5 for details). Programs are sets of Marketing Automation flows put together with the aim to reach one particular business objective across the customer life cycle. Marketing Automation is suitable for companies that manage important volume of customer interactions across channels and devices with limited resources.
  5. 5. 5 Table of content 1 Introduction ......................................................................................................2 1.1 Preface ............................................................................................................... 2 2 Management Summary .....................................................................................3 3 Table.................................................................................................................9 3.1 Table of illustrations .......................................................................................... 9 4 Thesis architecture .......................................................................................... 10 4.1 Why this topic? ................................................................................................ 10 4.2 Practical relevance........................................................................................... 11 4.3 Thesis structure................................................................................................ 12 4.4 Objectives of the thesis.................................................................................... 12 4.5 The research question ..................................................................................... 12 4.6 Theoretical foundation .................................................................................... 12 4.7 Methods and procedure.................................................................................. 13 4.8 Thesis thread summary.................................................................................... 14 5 Introduction to Marketing Automation............................................................ 15 5.1 History.............................................................................................................. 15 5.2 Today................................................................................................................ 18 5.3 Definitions........................................................................................................ 18 5.4 Other forms of business automation............................................................... 20 5.4.1 Sales automation...................................................................................... 21 5.4.2 Service automation................................................................................... 21 5.4.3 Advertising automation (programmatic advertising)............................... 22
  6. 6. 6 5.4.4 Benefits of Marketing Automation........................................................... 23 5.4.5 How does Marketing Automation differ from CRM?............................... 24 5.4.6 For whom is Marketing Automation most relevant?............................... 26 5.5 Marketing Automation theoretical models..................................................... 26 5.5.1 Lead to revenue management by Forrester............................................. 27 5.5.2 The strategic business question according to Carter’s model ................. 30 5.5.3 Irina Heimbach’s model............................................................................ 32 5.6 Enhanced New Marketing Automation Model................................................ 33 5.6.1 The campaign management..................................................................... 34 5.6.2 Marketing Automation Rules ................................................................... 34 5.6.3 Data Management platforms ................................................................... 36 5.6.4 Data collection.......................................................................................... 38 5.6.5 Data processing ........................................................................................ 39 5.6.6 Activation.................................................................................................. 42 5.6.7 Application example................................................................................. 43 5.6.8 Summary................................................................................................... 46 6 Research.......................................................................................................... 47 6.1 Study design..................................................................................................... 47 6.1.1 Desk research ........................................................................................... 47 6.1.2 Qualitative Content Analysis .................................................................... 48 6.1.3 The researched questions ........................................................................ 49 6.1.4 Sampling ................................................................................................... 49 6.2 Research findings............................................................................................. 51 6.2.1 The root causes and benefits for implementing Marketing Automation 51
  7. 7. 7 6.2.2 System architecture.................................................................................. 53 6.2.3 Data Management.................................................................................... 54 6.2.4 Organization & Processes......................................................................... 55 6.2.5 Marketing Automated, most efficient Rules & Flows .............................. 57 6.2.6 Best practices recommended by the interviewees.................................. 61 6.2.7 Mentioned obstacles and challenges by interviewee.............................. 63 6.2.8 What is next for Marketing Automation? ................................................ 64 6.3 Discussions....................................................................................................... 66 6.3.1 Summary of the researched questions .................................................... 70 6.4 Conclusions ...................................................................................................... 74 7 Appendix......................................................................................................... 76 7.1 Interview guide ................................................................................................ 76 7.2 Transcript of interview 1.................................................................................. 79 7.3 Transcript of interview 2.................................................................................. 90 7.4 Transcript of interview 3.................................................................................. 98 7.5 Transcript of interview 4................................................................................ 105 7.6 Transcript of interview 5................................................................................ 112 7.7 Transcript of interview 6................................................................................ 118 7.8 Transcript of interview 7................................................................................ 125 7.9 Transcript of interview 8................................................................................ 129 7.10 Transcript of interview 9................................................................................ 137 7.11 Transcript of interview 10.............................................................................. 145 7.12 Transcript of interview 11.............................................................................. 150 7.13 Transcript of interview 12.............................................................................. 155
  8. 8. 8 7.14 Codification of transcripts.............................................................................. 163 8 Bibliography.................................................................................................. 274 9 Declaration of Authenticity............................................................................ 277
  9. 9. 9 3 Table 3.1 Table of illustrations Illustration 5-1 - References of Marketing Automation occurred 1975 - 2008 ............. 15 Illustration 5-2 - First Marketing Automation Vendors (Source: Marketing Insider)..... 16 Illustration 5-3 - Closed-loop marketing cycle................................................................ 23 Illustration 5-4 - How is Marketing Automation different from CRM ?......................... 24 Illustration 5-5 – The L2RM Process (Source: Forrester Research, Inc.) ........................ 28 Illustration 5-6 - The strategic business questions from Carter's model ....................... 31 Illustration 5-7 - General Framework of Marketing Automation................................... 32 Illustration 5-8- The Enhanced New Marketing Automation Model.............................. 33 Illustration 5-9 - Functional aspects of DMP (Source: Comprendre les DMP, 2015)..... 37 Illustration 5-10 - Scoring concept (Source: EC4U, Delphine Arvangas)........................ 40 Illustration 5-11 - Media optimization and scoring (Source: Converteo, 2015)............. 41 Illustration 5-12 - The 6 steps of the customer life cycle............................................... 44 Illustration 5-13 - Examples of Marketing Automation flows ........................................ 45 Illustration 6-1 - Study design for qualitative content research .................................... 47 Illustration 6-2 – 12 interviewers’ sample list................................................................ 50
  10. 10. 10 4 Thesis architecture 4.1 Why this topic? The major motivation in choosing this topic lays on the on-going improvement of the consulting and tools I want to provide to Lindt & Sprüngli subsidiaries to grow their business. In August 2014, I had required to attend the program “Master of Advanced Studies in Customer Relationship Management (CRM)” of ZHAW in Zurich. At the time, I had discussed the following elements to convince my management to support me in this endeavour. 10% of all retail sales will be transacted online by 2020. In 2016, 50% of all purchases (in-store and online) will be influenced by digital touch points. For Lindt & Sprüngli AG, transforming its organization to fully embrace Digital and CRM is a critical factor in succeeding to grow market shares faster than the market and require a deep understanding of CRM and multi-channel strategies. Since 2008, Lindt & Sprüngli has continuously invested in building up a large community of consumers across several social and sales channels such as e-commerce and Retail stores, Mobile, Newsletters, Facebook, YouTube, Twitter. This growing volume of customer contacts makes its management more complex and hazardous especially across several countries. Lindt & Sprüngli needs more integrated tools, processes, and know-how to face these changes. We all observed the growing importance of digital marketing touch points for our consumers and the impacts on organization. These changes imply that we consider not just our target groups as whole homogenous segment but as single direct customer with particular needs. We must slowly move away from “One to Many” or mass towards “One to One” communication in real-time. I’m convinced that soon, not only knowing consumer’s needs and profile will be crucial to succeed in the business, but also to maintaining a high quality dialogue with our customers. This will become a key objective for all leading companies. By choosing this online educational program, I would like to better support Lindt &
  11. 11. 11 Sprüngli AG in implementing concrete CRM solutions, most probably for our retailing organizations and help our teams collect, manage and analyse our consumer data in order to enhance Lindt brand equity and grow sales. Today, I simply have put a name on what I believe may help my company to achieve this objective. Marketing Automation. I am proud to share with you the results of my research and I hope you will find it useful. 4.2 Practical relevance While literature provides an important volume of information about CRM, it is more difficult to find academic literature about the functioning of Marketing Automation in the context of CRM. The empirical proof that Marketing Automation is helping companies to save costs and increase revenue generation is missing from an academic point of view. More, our preliminary researches have shown no or very little standardized and structured researches about the impact of Marketing Automation on revenue generation and marketing efficiency. The existing literature provide guidance about the implementation of Marketing Automation software but it lacks a standardized model to highlights some of the key components and processes to realizing the true value of Marketing Automation as a marketing strategy.
  12. 12. 12 4.3 Thesis structure The first part of the paper introduces the purpose of the thesis and its objectives, construction and overall goals. The second part is dedicated to an introduction of Marketing Automation through history, application, process and methods including key existing theoretical models that we used to establish the “Enhanced New Marketing Automation Model” described in chapter 5.6. The Third part is dedicated to the findings, discussions and conclusions by analysing the practice of interviewed companies using Marketing Automation. 4.4 Objectives of the thesis The objective of the thesis is to help the reader to understand how Marketing Automation strategies leads to CRM leadership and most importantly increase marketing efficiency and revenue generation. By strategy, we mean the mastering of means, skills, tools and processes that answer a company strategic business questions. 4.5 The research question The research question for this paper is: What are the required means, skills, tools and processes for successful Marketing Automation, leading to marketing efficiency and revenue generation? 4.6 Theoretical foundation The fundamental reason for companies wanting to build relationships with customers is economic. If they manage their CRM well, they have two important key business benefits as follow: Marketing efficiency Marketing Automation is in fact a derivative from the business process automation defined as a process of managing information, data and processes to reduce costs, resources and investment. Business Process Automation increases productivity by
  13. 13. 13 automating key business processes through computing technology (Technopedia, 2015). Literature also stress out the importance of keeping existing customer buying over customer acquisition, especially from the cost perspective. It costs a company six times more to sell a product to a new customer than an existing one (Dyché, 2008). Marketing Automation benefits will ultimately improve lead management, nurturing, provide measurable results, enhance targeting and personalization with seamless campaign execution, increasing efficiency and productivity, align marketing and sales, support CRM, develop business intelligence and improve improved user engagement (Regalix, 2014). Better Financial performances Companies generate better results when they manage their customer base in order to identify, acquire satisfy and retain profitable customers. These are key objectives of many CRM strategies (Buttle, Customer Relationship Management: concepts and technologies, 2011). Organizations that embrace marketing metrics and create data- driven marketing culture, have a competitive advantage that results in significantly better financial performances than of their competitors (Jeffery, 2010). 4.7 Methods and procedure To answer the research questions, desktop research will be conducted in order to get in-depth understanding of the research field, in particular the Marketing Automation history, principles, definitions, processes and tools. The desk research will build the base for the qualitative research. This paper will focus on the main theories and models from which Marketing Automation has derived from and can be found in chapter 5.5. Literature research included books, peer-reviewed and non-peer reviewed articles from various journals and studies from consulting and research companies. The purpose of the data collection is to identify the current state of research in this particular research field. Because the research questions cannot be answered by gathering information exclusively from desk research, a qualitative research study will be conducted. Part of the data used in this paper will be collected in performing interviews with Marketing
  14. 14. 14 Automation experts. The questionnaire used for the qualitative content research will be designed according to the “Enhanced New Marketing Automation Model” proposed in the chapter 5.6. The aim of the interviews is to meet various Business to Consumer and Business to Business companies’ professionals using Marketing Automation across various industries of different sizes and countries such as CRM, Retail e-commerce or marketing departments, the detailed list of the interviewees can be found in chapter 6.1.4. The interviews will be transcribed and interpreted using the technique of qualitative content analysis exposed in chapter 6.1.2. 4.8 Thesis thread summary The below illustration will give the readers the lead thesis architecture while reading this thesis. Illustration 4-2 - Thesis thread
  15. 15. 15 5 Introduction to Marketing Automation 5.1 History According to Heimbach, the term Marketing Automation as we know it today, was first introduced by John D.C Little in his presentation at the 5th Invitational Choice Symposium UC Berkeley 2001. Little refers to it as the automated marketing decision support on the Internet. Little formulated its essence with this phase: ‘‘What do we tell retailer X to do when customer Y arrives on Monday morning?”. However, Marketing Automation term seems to be older than that 2001. In using Google Books Ngram Viewer, we have created a graph showing how Marketing Automation have occurred in a corpus of books in between 1975 and 2008. The graph below show that Marketing Automation is not a new idea and seems to have been used since the late seventies. Illustration 5-1 - References of Marketing Automation occurred 1975 - 2008 This discovery led us to research more in depth about the term Marketing Automation and we found out that the very first mention appeared in 1962 when Charles R. Goeldner published an article about it. Automation in marketing is taking several forms, such as automatic stores, vending machines, electronic data processing, and automatic warehousing (Goeldner, 1962). While automation was existing at the time in only a small
  16. 16. 16 experimental number of institutions, the author believed at the time it would have a profound influence on the future of American marketing institutions. The history of Marketing Automation as we know it today, really started in the late 1990s. The first rise and fall of Marketing Automation was tied to the dot.com boom and burst. The 1990s saw a myriad of Marketing Automation vendors come up with solutions on the market including SAS, UNICA and Eloqua to name a few. After the burst only a few survived as standalone vendor such as SAS. Some of them are still in the market today, such as UNICA which is part of IBM or Eloqua part of Oracle. The middle of the 2000 marked several shifts for Marketing Automation when next generation vendor like Infusion Soft or Marketo emerged. Over the next years, the pioneers’ s success inspired a number of other competitors to enter the market. These included companies such as Pardot now part of Sales Force. Illustration 5-2 - First Marketing Automation Vendors (Source: Marketing Insider) In the late 2000s, Marketing Automation started to speed up in awareness and interest, essentially due to three main reasons. First, changing buyer’s behaviours forced companies to change how they sell and market. Before the Internet and social networks, buyers had limited options to obtain the products and services information they wanted, so the seller controlled the buying process. Then customers moved to the power position. They could get the information they wanted on their own by delaying the initial contact with the sale representative until they know as much or even more than the salesperson. To address this challenge,
  17. 17. 17 Marketing Automation started to play an increasing role in the revenue process. They nurtured relationship with early stage prospects until they became ready (Jon Miller, 2013). Nevertheless, how do you manage individual dialogue with hundreds of thousands, even millions of potential customers? This is precisely why having a Marketing Automation platform became so critical in the mid-2000. There was no any other way to keep up with the demand of modern marketing. The second factors is linked to the 2008 crisis, which forced companies to change their approach to market in favour of more lead and revenue generation focus (Jon Miller, 2013). Almost all companies have been affected by the crisis. While smaller companies literally searched to cut cost and headcounts to reinvest in lead to revenue generation management, larger companies have seen potential by introducing Marketing Automation not only to survive, but also take advantage of this evolution to reinforce their leadership. They invested in technology that automated and streamlined critical revenue process. Particularly in crisis time, when marketing considered as expenses, measurability became key to demonstrate efficiency across digital channels in order to reallocate marketing budget to higher ROI channels. Marketing Automation became also more popular because of its capability to prove return on investment. The third trends that favoured the development and adoption of Marketing Automation Software came from a new software delivery model called “Software as a Service” (SaaS). This means that marketing managers could access any software through their browser without or very little support of their IT. Because these software are sold using the subscription fee model, marketing manager could buy it using marketing expenses budget rather that capital investments allowing them to control and anticipate their expenses. These three reasons strongly contributed to make from the newly Marketing Automation offer a rapid adoption in the 2000s. Between 2010 and 2014, there was over $5.5 billion worth of acquisitions made in the Marketing Automation industry. The main reasons were simple. Fragmented marketing systems will need to be replaced by integrated marketing suite (Raab, 2011). Larger Marketing Automation vendors started to acquire smaller. The largest one was
  18. 18. 18 Salesforce’s ‘Russian doll’ acquisition of ExactTarget for $2.5 billion, after ExactTarget acquired Pardot for $95 million (Taylor, 2015). 5.2 Today Marketing Automation software editors are providing today more options than ever to face more complex customer lifecycle, a broader array of digital marketing channels and unprecedented volume of customer data. Marketers who implement Marketing Automation increased their sales-pipeline contribution by 10% (Vendors, 2014). Marketing Automation software vendors are now benefiting from their success, as systems Revenues for B2B Marketing Automation systems will grow 60% to reach $1.2 billion in 2014, according to Raab Associates. Industries such as telecommunication, consumer packaged goods manufacturer and financial services providers now comprise as much as 75% of the customer base for several vendors. Software Advise, a division of Gartner found that only 9% of potential software buyers currently use a Marketing Automation system. Just 3% of micro-businesses and less than 10% or large firms use Marketing Automation software, according to Raab Associate. Marketing Automation vendors are also taking a certain number of strategic approaches, including acquisition, mergers and market repositioning to leverage the opportunities leverage by these challenges. 5.3 Definitions The various definitions below indicate how differently Marketing Automation may be defined across experts or vendors. In writing this paper and while conducting the research interviews, we have used the following main definition: Main definition: Marketing Automation is a category of technology that allows companies to streamline, automate, and measure marketing tasks and workflows, so they can increase operational efficiency and grow revenue faster (Jon Miller, 2013). We have selected the above definition as the lead definition for writing this paper and in designing the research study. One of the reason was that it was generic enough to
  19. 19. 19 encompass all forms of business automation. This first definition underlines the facts that Marketing Automation’s main benefit is operational efficiency and revenue growth, which is one of the initial assumption of the paper. Marketing Automation is still new and complex enough that experts themselves struggle to agree on a unique definition. Therefore, we would like to propose additional definitions to complete the main one above: Definition two: Marketing Automation software collects and uses data to send personalized messages to contacts at different times based on their actions (Taylor, 2015). This second definition underlines the process, starting by data collection in order to send personalized message and to engage prospects at different times based on their actions. The definition is very close to Heimbach Marketing Automation workflow described further in chapter 5.5.3. The definition suggests that data management, personalization of content and action in time are the central elements of the Marketing Automation processes. Marketing Automation here allows marketer to send the right message to the right person at the right time because it is triggered by an action. We could reasonably think that a phone call or a one-to-one conversation may do the same. In fact, what Marketing Automation offers on top is the management of an important quantity of conversations at the same time, automatically and without hiring a horde of staff. Summarized, Marketing Automation allows companies to solve a fundamental business issue: scaling the ability to communicate with a large volume of contact in a personalized manner. Definition three: Marketing Automation focuses on the lead acquisition and demand generation activities within a marketing group, as opposed to the sales activities where CRM systems as a whole tend to focus. Simply put, these tools automate marketing processes — everything from strategic planning and campaign design to customer segmentation, lead generation, nurture campaigns, prospect scoring, and closed loop analytics (Schwartz, 2015). This third definition highlights the different approaches of marketing and sales, marketing being focused on acquisitions and sales on revenue growth. It contextualizes Marketing Automation in relation to CRM, making of both methods a complementary approach. Some key fundamental functionalities are listed
  20. 20. 20 here and will be further exposed in the paper, especially in chapter 5.6. It also underlines the automation of marketing processes, from strategic to operational part and suggests the retro-looping functioning of it. 5.4 Other forms of business automation Without well-designed and applied operational processes, there is little possibility of implementing the CRM strategy (Buttle, Customer Relationship Management: concepts and technologies, 2015). This capability often require IT investments in the following four fundamental solutions: Sales force automation, Marketing Automation, Ad automation and Service automation. The purpose of that paper is to introduce Marketing Automation; therefore, it is important to be able to contextualize the role of each well-established type of automated business processes below. Business automation which Marketing Automation belongs to has always been a strategic aspect of business operations. Many organizations today are relying on upon digital technology for a wide range of application and automation has moved into a central position in the IT investment landscape (Paul, 2015). The general principles of automation in the modern workspaces include the deployment of solutions and frameworks that will reduce and rework inefficient processes, improve the accuracy and free up resources to focus on performance improvement (Paul, 2015). According to the research institute Gartner, by 2020, customers would manage 85% of the relationship with a company without even talking to a human (Gartner, Gartner Customer Summit, 2011). Automation value does not rely relies on sales growth, but for 75% on costs saving leading to resources reallocation (Fétique, 2015). Isn’t Marketing Automation everything that a computer does for us in marketing? Let’s think of a website: once planned, programmed and put in production, what isn’t automated? It is available 24/24 a day, loading up webpage without the support of a horde of staff, collecting user data, sending out emails or invoices. All these tasks are automated! A website is fully automated, and it is part of the marketing arsenal. Is this Marketing Automation? Yes it is. So why are we talking about Marketing Automation here? In fact, Marketing Automation is an umbrella concept. Before Marketing Automation vendor agreed on a
  21. 21. 21 shared and widely adopted name, some vendors or consultant tried to impose other names such as Forrester “Lead To Revenue Generation (L2RG)” or “data marketing”. Since the growing interest of Business to Consumer companies for it and the increasing number of customer contact across digital channels, Marketing Automation has been adopted as an umbrella name, which regroup several marketing disciplines and methodologies. Here are the other forms of business automation: 5.4.1 Sales automation Sales force automation can be define as follow: Sales force automation is the application of computerized technologies to support salespeople and sales management in the achievement of their work-related objectives (Buttle, Customer Relationship Management: concepts and technologies, 2015). Most of Sales Force Automation software are designed to collect, store analyse and distribute user customer-related data for sales purposes. This software’s enables managers to operate the following key activities: account management, contract management, document management, event management, lead management, order management, pipeline management, and product configuration, amongst other things. Here the primarily focus is to support essential sales processes. According to Buttle, most benefits for using sales automation ar more cash flow, shorter sales cycles leading to faster inventory turnover, proved customer relationships, accurate management reports, increase sales revenue, market share growth, higher win rate, reduced cost of sales, more closing opportunities and improve profitability (Buttle, Customer Relationship Management: concepts and technologies, 2011). 5.4.2 Service automation Service automation can be defined as follow: Service automation is the application of computerized technologies to support service managers, customer service agents in call centres, help-desk staff and mobile service staff operating in the field, in the achievement of their work-related objectives (Buttle, Customer Relationship Management: concepts and technologies, 2015). Customer service department are
  22. 22. 22 responsible for managing inbound call centers, operations, complaints handling and resolution, order entry and processing, providing field sales support, managing outbound call center operations and acting as liaison to other departments. When service is delivered through a central call center, in a multi-channel environment there need to be a tight integration between various communication systems including telephony, email, and the web. Access to the right customer-related data to enable the service agent to identify and fix the issue promptly is critical to the delivery of responsive customer service. 5.4.3 Advertising automation (programmatic advertising) Advertising deals used to be made by phone, fax and e-mail. Now much of that work is being done on purpose-built digital marketplaces. Traditionally, companies are firing message at huge audience on print or TV, hopping they’d reach out the right audience. Ad trading desk are helping to do that more exact. Known as “programmatic advertising,” this process involves computerized systems to sell online ad space to advertisers and their agencies. It is comparable to a stock market, instead of trading shares, these markets trade digital ad space, or impressions (Krashinsky, 2015). It is another form of automation, which is reshaping the advertising industry. Today, about half of the advertising expenses is automated, especially for display ads. Automated trading increase efficiency by reducing costs and increasing targeting efficiency. An advertiser or representative add agency registers at the trading desk, also known as “Demand-Side-Platform” to place an ad that target a specific audience. E.g. a Swiss 35- 44 woman who likes French cooking, without kids, speaking German and living in the canton of Zurich. They also put in the price range they are willing to pay for that digital ad space. That information is processed in the ad exchange, also known as “Supply-Side- Platform” where ad inventory’s of publishers is offered, and in fractions of a second, the auction is done and the winning bidder’s ad is placed on a website. Meanwhile, dozens of ad-tech companies are fighting for a piece of this market, the industry is call to evolve a lot. In combination with its Data Management platform, which is a key component of
  23. 23. 23 Marketing Automation - see chapter 5.6.3, the advertiser will be able to automate the ad buying process based on educated information extracted from its customer database. 5.4.4 Benefits of Marketing Automation Marketing Automation is all about understanding customer needs and meet their preference (Buttle, Customer Relationship Management: concepts and technologies, 2015). Customer develops a stronger sense of emotional and behavioural identification with the company when they experience offers and communications that base on deep understanding of their needs and preferences. One of the very first benefit when talking about IT enabled CRM programs is cost saving. This is essentially due to more formalized and standardized processes, generating operational costs savings. Normally, a company willing to introduce a customer-centric-strategy invests primarily in building a single view of the customer also known as “SVOC”. This approach integrate all form of data from all operational units that involves customers such as sales, marketing customer and customer service in order to create a unified view of the customer interactions with the company. Once this is in place, the company’s employee may engage the customer one- to-one based on his activity. Once this customer-related data infrastructure is in place, companies may introduce analytical software and develop the ability to data mine in order to produce actionable insights. Enhanced marketing efficiency. Marketing Automation allows marketer to automate what is known as the closed loop marketing (plan-do-measure-Lear cycle) as illustrated in the figures 5.3. Closed loop marketing approach makes sure companies learn continuously from their marketing initiatives, achieving higher level of marketing effectiveness. Another source of efficiency is the identification of inefficient or falling marketing initiatives in order to reallocate resources to more successful activities. The increasing number of customer contacts and sales promotions companies must face today makes the Illustration 5-3 - Closed-loop marketing cycle
  24. 24. 24 advertising campaign management much more complex and challenging. This main idea behind the replication of marketing processes is that it should delivers greater control over costs. Unsurprisingly, manual processes are often the source of errors and inefficiencies. Consequently, automation of process is a way to reduce costs (Buttle, Customer Relationship Management: concepts and technologies, 2015). Marketing Automation allows companies to execute hundreds of campaign and events simultaneously across multiple channels without the proportional increase of costs and complexity in running the marketing activities. Marketing plans are often designed months ahead. Marketing Automation allows manager to respond more instantly to opportunities even if they are not part of a plan. Some features enable firms to engage in real-time, responding immediately to an identified opportunity. For example if a user is visiting a given product category for the third time in the same week, marketer can send and automated offer with a reduction voucher. 5.4.5 How does Marketing Automation differ from CRM? Illustration 5-4 - How is Marketing Automation different from CRM ?
  25. 25. 25 Marketing Automation and CRM are very similar marketing methods that have much aspect in common. Having long proved their strategic value, CRMs are now an essential tool for hundreds of thousands of businesses in almost every industry (Peterson, 2015). CRM is not a technology but a strategy. It is nevertheless very hard to do without technology (Kirby, 2015). Even if CRM is often considered as a technology, it is more a business philosophy or a business model. CRM is a business model, which covers people, customers, strategy, organization, processes and technology. It integrates all these elements in the direction of the customer satisfaction with as a main objective a balance between cost and return on investment (Huldi, 2015). In most people’s mind, CRM is more a software or a tool than a strategy. In fact, CRM software is a category of software that covers a broad set of applications and software designed to help businesses to manage customer data and customer interaction, access business information, automate sales, marketing and customer support and manage employee, vendor and partner relationships (Beal, 2015). From that perspective, CRM covers Marketing Automation. From a functional perspective, CRM systems typically do not provide functionality for email marketing, prospect behaviour tracking and marketing program management. It is true that many CRM systems can be customized to operate these tasks like automated campaign flows, lead scoring and lead deduplication, but it is hard and expensive. In the end, Marketing Automation focuses on the need of marketing departments, lead generation while CRM provides must-have solution to the sale department. CRM software is a database for storing user or customer data and managing the revenue process. Alone, the company will have the basic ability to store contacts and track sales stages, but limited insight into the buyer’s journey (Peterson, 2015). The buyer’s journey start long before they become a customer. With no information on where the leads came from, what their interests are, and how they have interacted with the various marketing touch points, the initial conversation will be a lot harder to navigate, analysed and understood. Technically, a Marketing Automation platform is in other word a lead generation engine without a CRM. Here, the perfect relationship between marketing and sales can be expressed — at least in part by the structural relationship between Marketing
  26. 26. 26 Automation and CRM. When both processes are integrated, this means the end of marketing and sales data silo for better operation alignment. Marketing can focus on bringing in qualified lead and tracking customer journeys across digital touch point before sales take the order completion with a full history. For sales, Marketing Automation delivers a high quality leads much closer to the completions status than ever. In short, CRM and Marketing Automation together should leads to reduced costs and increased revenue. 5.4.6 For whom is Marketing Automation most relevant? Marketing Automation is best suited to companies with predictable communication that could be converted into a process with a large volume of users, subscribers or customers (Taylor, 2015). The more contact the company has, the more potential impact the software has. A company business model will influence the type of relationship between a customer and the merchant. Retailers with direct customer contact will have greater opportunity to collect user data compared to wholesaler. With few or no direct contact with end consumer due to the nature of its distribution model the wholesaler will traditionally focus on mass media. As a result, online retailers are in general more interested in Marketing Automation than companies without an online shop (Heimbach, 2015). 5.5 Marketing Automation theoretical models The aim of this chapter is to introduce to the readers a fundamental theoretical concept, which influenced the development of Marketing Automation workflow, and depict the fundamental processes used for it. The model we propose is inspired from 3 already existing model as following: 1. The Lead To revenue Management Model by Forrester 2. The SWAT Iteration Framework of Carter 3. Heimbach’s model
  27. 27. 27 To start, we will introduce the “Lead to revenue management” (L2RM) concept developed by Forrester Research which represent two parallel closed loop journeys. Marketing Automation was originally used and designed for Business to business industries but is today largely adopted in business to consumer’s context because of the explosion of customer touch points and contacts. We will use it as a leading model. The concept is particularly interesting because it puts in parallel the journey of the buyers and the seller, aligning the marketing tasks (attraction) and the selling tasks (deliver). To enrich the Forrester model to Marketing Automation, we have selected the very first step of the “SWAT Iteration Framework” of Carter. Carter in his book “Actionable Intelligence, a Guide to delivering business results with big data fast” outlines the importance of the definition of a strategic business question before processing the data, visualize segments and to take action. Without clear business, questions to solve in mind, the implementation of Marketing Automation rules may lead to poor results. Finally, we have chosen to present a third concept taken out of the paper “Marketing Automation” of Irina Heimbach, which attempt to depict the general framework of Marketing Automation. This recent paper brings to our attention six important elements, part of a workflow specific to Marketing Automation. Taking the best of each of the three existing model, we will design the “Enhanced New Marketing Automation Model”. 5.5.1 Lead to revenue management by Forrester Initial lead-to-revenue management automation solutions were developed to bridge a gap between marketing or lead generation activities (e.g., website, online forms, trade shows, direct mail, telemarketing, and email campaigns) and selling activities that were managed by a CRM system (e.g., closing the deal). The opportunity to calibrate marketing spend to revenue generation was a significant driver of L2RM. The below figures show Lead-to-revenue management is a set of disciplines that can be strongly supported by Marketing Automation, but marketers need to focus on the below processes to make L2RM automation initiatives a success.
  28. 28. 28 Illustration 5-5 – The L2RM Process (Source: Forrester Research, Inc.) This info graphic, based on independent research from Forrester, gives a visual representation of how marketers can make the most of their lead to management investments by developing a Marketing Automation road map that meet buyers journey. The process displays two major processes. One is on the buyer’s side defined as the buyer’s journey and the second one is on the merchant side, the Lead to revenue management (L2RM) process. For each five phases of the buyers ‘journey the figures show a corresponding merchant process. 5.5.1.1 The buyers’ journey Buyers have different interest at different steps of the buyer’s journey. It is crucial to get the buyers question that needs to be addressed at each stage. It is also important to understand what will trigger a buyer to move to next stage and identify the barrier for the progression. Here is the buyer’s journey phases explained: Discover: At this stage, the buyers is asking himself, what outcome am I going to achieve? What need or pain am I trying to fix or improve? Typically, the buyers
  29. 29. 29 determines the need to solve a problem. The budget for the solution is determined and some approaches to solving the issue are addressed. Explore: Buyers will start exploring and identifying possible solutions, product or services, choosing an approach, consider risks and start comparing alternatives. At this stage the buyer will be starting select some vendors and check for references or read review for example. Buy: A this stage, the buyers define a shortlist of vendors that are invited to bid, vendors submit offers, solution is acquired. Engage: This phase corresponds to the after sales. After the product acquisition, the customer may get in touch with the vendor, will ask for support, and possibly upgrade its product. The moment is crucial because this is at that moment that he will adopt the product if its experience and results are satisfying. Advocate: If the buyers has adopted the product, he had a positive experience of the product or services; he might turn into an advocate. Advocate are the most wanted brand influencers. They are the customer that advocate the brand because they are passionate about the product or services and respect the company. 5.5.1.2 The Lead to Revenue Management Process (sell) The closed-loop can be spited in two major phases. Attract and deliver. Initial lead-to- revenue management automation solutions were developed to bridge a gap between these two phases. Attract corresponds to the typical marketing activities with brings in qualified leads which are mature enough that they can be approached by the selling team in order to close the deal. This phase is structured in two sub-phases called capturing and nurturing: Capture: The capture phase encompasses all marketing activities that will help you clarify who your best customers are, identify what they need and understand how to connect with them. Lead nurturing: Is the process of building effective relationships with potential customers throughout the buying journey (Rothman, 2015). Note that Marketing
  30. 30. 30 Automation software editor Marketo distinguishes lead nurturing which is an evolved version of drip marketing. Drip marketing has in common the send out of communication such as email, direct mail or phone call, but it does not take into consideration the activity of behaviour of users, because it is static and non-adaptive. For example, drip marketing does not take into account personal preferences and actions and cannot deliver the same value as lead nurturing, because it is adaptive and personalized. The second phase is the deliver status, which starts with: Sell: This covers the closing phase. It includes trial periods, bidding, price negotiations, signing of contracts, and delivery of the product or service being sold. Build advocacy: A customer advocacy policy encompasses all aspects of customer contact, including products, services, sales and complaints. It is a total commitment towards customer satisfaction. The idea is that if a customer is happy with the company, they will pay more for the service. As mentioned above, if the customer had a positive experience of the product or services, he will turn into an advocate. 5.5.2 The strategic business question according to Carter’s model Business discovery is the critical step in transforming the unstructured mass of data available into actionable intelligence (Carter, 2014). Carter is bringing up an interesting element and invites us to think about the strategic questions that we are trying to solve before implementing any automated marketing tasks. Merchants today are collecting large volumes of data across many channels leading – sometimes to confusions and complexity. Every business has its priorities and overall strategy. Direct your effort depending on your overall strategic priorities.
  31. 31. 31 Illustration 5-6 - The strategic business questions from Carter's model Therefore, we should not try to collect all the data, but only focus on the “burning platform” (Carter, 2014). The strategic business questions – highlighted in blue in the below chart - should be a guide to ensure that the priority of the project remains high. Selecting on question to focus on allows the rapid and iterative development to occur as the business and technology team can focus. Clarity of purpose allows sponsors and supporters to get behind the project because they will clearly see the opportunity to deliver tangible results. For Carter, while many people have been advocating the mass collection of data, actionable intelligence suggests you to choose a different approach. The data collection needs to be focused solely on the strategic question (Carter, 2014). This enables the acquisition team to collect and review quality and relevant data. In other words leading data processing method answers the questions: “What kind of data do we really need to answer the strategic questions? Where can I find it? What is the IT infrastructure that we need? Who are the people with the required skills to analyse it? How can we capture the data in a cost effective manner? Focussing on the required data should facilitate the acquisition, lower cost and increase feasibility. Therefore, we propose to add the strategic business question to the Forrester model to complete it. A revised version of it will be proposed in the chapter 5.6.
  32. 32. 32 5.5.3 Irina Heimbach’s model Irina Heimbach with her “General framework of Marketing Automation” as presented below, introduces some interesting element that will complement the L2RM model as well: Illustration 5-7 - General Framework of Marketing Automation Current and stored information. Here Heimbach introduces the notion of stored and current information. As seen in the chapter above, availability of data is a condition in the context of Marketing Automation. Data remain an important element beyond the analysis; since all automated marketing actions are direct responses to existing, incoming or changing customer/user information (Heimbach, 2015). These data may originate from a customer database, but may as well stem back to tracked user journeys or clickstream data on the website in real-time. We assume she refers to synchronous and asynchronous, because both tracked user journey or clickstream data can be stored into a database. Monitoring interfaces and rules. This is the place where marketer controls the performance and creates the rules. If for example several options are possible, the Marketing Automation software will be able to apply these options based on particular events based on contextual or behavioural user information. This optimization process
  33. 33. 33 and the performance of the above-mentioned rules can be monitored and adjusted by the manager at any time. The literature also talks about Campaign Management or marketing orchestration. Set of rules. Once the marketing owns some user or customer data, stored or collected in real time, the marketer may create marketing rules. These rules are in other words some marketing processes, which are pre-defined in the campaign management system. Campaign Management will be an important element added to the original Forrester model presented later and further developed in the chapter 5.6. 5.6 Enhanced New Marketing Automation Model As mentioned earlier, we would like to propose below the “Enhanced New Marketing Automation Model” which derived from the Forrester L2RM model, enriched with the Carter and Heimbach models presented earlier. In this enhanced model, we have added two additional elements: the business questions and the campaign management component. Illustration 5-8- The Enhanced New Marketing Automation Model
  34. 34. 34 The business question is a critical element and the starting point of all Marketing Automation model as exposed in the chapter 5.5.2 above. The campaign Management system is situated at the heart of all Marketing Automation; this is where rules and flows are orchestrated and managed to activate customers. 5.6.1 The campaign management Today, Marketers are using a wider range of communication channels to reach prospects and customers with relevant messages on their preferred devices. Paid and organic advertising campaigns are becoming an increasingly important feature for campaign management within their Marketing Automation platform. As results, the Marketing Automation systems now includes two core mechanisms: the “Data management platform or DMP” and a “set of rules” like Heimbach models suggests earlier in chapter 5.5.3. We have grouped them under “Campaign management” and can be defined as follow: campaign management is the technology-enabled application of data-driven strategies to select customers or prospects for customized communications and offers that vary at every stage of the customer lifecycle and buyer readiness (Buttle, Customer Relationship Management: concepts and technologies, 2015). Campaign management lays in the heart of the Marketing Automation process, because it put together the planning, the implementation and the measuring of communication programs towards targeted prospect or customers. In our newly created model, set of rules, data management platform and analytics are the core elements of campaign management. 5.6.2 Marketing Automation Rules This is the orchestrating element of Marketing Automation process. Before running a campaign, it has to be designed and planned. Workflows established in the “Set of Rules” set clear order in which tasks have to be performed. If we want to pick a representative image of Marketing Automation, it would be one of these flow-like diagrams, e.g if a customer visits one particular page, then send him this email — if he is a qualified lead send him that promotion — else wait 2 days and send them this other email — if we
  35. 35. 35 know his email address — else cookie them for display advertising retargeting (Taylor, 2015): Here are the key elements of the workflow: Illustration - 1 Marketing Automation flow chart from Oracle Eloqua The trigger: What causes the workflow to start? Event based marketing also called trigger marketing is a form of marketing that identifies key events in the customer and business lifecycle which trigger a communication of offer. When an event occurs, a customer specific marketing activity is undertaken (Ramshaw, 2015). The cause may be an IP address (for location-based marketing), the usage of a particular browser, a device or the time. Timing: This is the time in between different steps of the flow. For example, a reminder is sent 12 hours after a user has abandoned his cart. Conditions: This defines what happen if a condition X is true or if the condition X is false. For example if a user abandons a shopping cart before payment, this triggers a follow- up reminder email aimed at converting the lapse browser into a purchase.
  36. 36. 36 Activation: What should be activated when the condition is true or false? This could activate the use of the customer-preferred medium. Campaign execution happens when the message is delivered through the selected communication channels. Mediums: Campaigns can be run across many different mediums independently, consecutively or simultaneously, such as display advertising, email, search, social media, website, outbound or inbound phone, text messages or mobile. Personalization in Marketing Automation context means that customers are known as individuals rather than demographic stereotypes. Personalization can happen in real time upon individual’s preferences or behaviours. Workflows or rules allows manager to plan, design, manage and monitor specific automated marketing campaigns, which are often complex and follow event based next- step rules. The most basic campaign management tools enable campaign workflow, audience segmentation and targeting and campaign execution. 5.6.3 Data Management platforms Since (Little, 2001) first formulation, the core motivation for implementing Marketing Automation has not changed: the lack of appropriate models while facing huge amount of data automatically collected by online companies. Digital channels today provides to companies new and valuable source of customer data such as historical, financial and behavioural data across multiple devices. Nevertheless, the multiplication of channels and data volume makes it difficult to gather, store, structure, analyse and action in a simple way. Data remain an important element beyond the analysis, since all automated actions are a direct response to existing, incoming or changing customer / user information (Irina Heimbach, 2015). Data management becomes crucial for companies when at least one of these three conditions are met: First, their customers have a complex customer journey and they are using several mediums to engage their brand such as email, web, mobile, store, customer support etc. Second, the company has customer data stored in different silos with various origins
  37. 37. 37 such as online and offline, leading to a poor customer single view. Finally, the company has response time issue when engaging which customer that it would like to improve. Illustration 5-9 - Functional aspects of DMP (Source: Comprendre les DMP, 2015) Data management offer the following fundamental benefits. It helps create a single customer view, providing ways to identify users, enrich their profile and action these across the digital landscape. It helps find new and high value audiences and monetise them. Drive efficiencies across multiple channels and devices. In fact, a DMP has the ability to help across the whole customer journey. Help marketers, and their media agencies, secure greater efficiencies in targeting display advertising (Bay, 2015). Data Management Platforms are especially good at optimizing the media buying process such as display, Search Engine Marketing, video advertising or social media and support greater personalization of and customization across the various touch points. The Data Management Platform represented above is concretely a software platform that enables the collection and the centralization of prospects and customers data. The platform can enrich the user records in re-assembling user data, in segmenting or scoring the value of each record and finally by activate the data to reach out users, prospects or customers. The three phase are described in details in the below illustration and the following chapters:
  38. 38. 38 5.6.4 Data collection Today, marketing people are primarily and in many cases exclusively engaging online and are closely aligning their effort with the key information found in their online behaviour. By analysing and understanding prospect online behaviour such as email responses, web pages view, social engagement and other core attribute, marketer have a wealthy of insights to personally guide prospects through the buying process. The DMP manages the process of taking structured data from a number of different sources and organizing it at the customer level or at the cookie level if the person is unknown. Various source of data may be aggregated in order to enrich the user records or profile, such as purchase history, socio-demographics, behavioural data such as website customer journey (tag management, analytics), web forms, explicit data such as demographics, social media data preferences, geo-localizations. Today, experts talk about three categories of data. First party data are the data collected from digital platforms such as websites, apps, data from CRM systems and from customers and their behaviours. Amazon, for example, uses its first-party data to show users products it thinks they might buy on its homepage. Second party data are data from partners who share their first-party data with other partner companies. For example, a large advertiser such as P&G might make a deal with a large publisher to gain access to its audience information. As far as P&G is concerned, that information isn’t “first-party” data because it didn’t collect it itself. But it isn’t third-party data, either, which is typically gleaned from a variety of places. Third party data are data from other sources such as websites, online newsletter or blogs which have anonymous behavioural data. For example, a third-party data provider might pay publishers (magazine, online newspaper) to let it collect information about their visitors, and use it to piece together detailed profiles about users’ tastes and behaviours as they move around the Web. This information can then be sold to advertisers to help them target their ad buys. Finally note that data reconciliation means also the process of assigning first; second and third party data that belong to a single user to a single record.
  39. 39. 39 5.6.5 Data processing In this chapter, we would like to introduce key methods to process the data. These tasks are normally performed into the Data Management Platform. Data normalization. Before to use the data, it is crucial to normalize the data. Data normalization is a process in which data attributes within a data model are organized to increase the cohesion of entity types. In other words, the goal of data normalization is to reduce and even eliminate data redundancy, an important consideration for application developers because it is incredibly difficult to stores objects in a relational database that maintains the same information in several places (Wembler, 2015). Progressive profiling. A typical data collection supported by Marketing Automation is the “progressive profiling”, enabling marketers to ask for information incrementally instead of all at once. Over time, leads will become more qualified because of their interaction with a website (and other digital properties) and will likewise deliver useful information to sales (Boush, 2011). Data reconciliation. Once the user record is normalized, the Data Management Platform can for example reunify two different records in one, for example when a unique user has visited a website browsing first a mobile then a desktop. Two main methods are in use: Deterministic is the method that is used when the users are registered, we call it also explicit as opposed to implicit. The Data Management platform knows the person has used the two mediums because he was identified. Probabilistic is the method that uses algorithm to determine whether the users have similar behaviour. Probability are based on e.g. IP address, screen resolution, time of connection, interest etc. The Benefit is to be able to provide users a seamless customer experience across devices and channels and for the merchant, to track user across channels and devices to understand its preferences. Data segmentation. A data management platform must enable the creation of segmented contact lists based on field values (e.g. title, level, department) and inferred data on location and activity (obtained through interactions with forms, company Web pages, emails, etc.) for use in automated programs and reporting (Decisions, 2015).
  40. 40. 40 These segments can be kept in a static list, reflecting their status when the segmentation was made, or automatically updated as contact data and activities change. Data scoring is a form of segmentation. Lead scoring is a shared sales and marketing methodology for ranking leads in order to determine their sales or activity readiness. The score leads is based on the interest a customer show for a company, their current place in the buying cycle and their fit in regards to the business (Maria Pergolino, 2015). Data scoring fundamentals distinguishes two major statuses: explicit and implicit data. Explicit scoring is based on information the prospect tells the company or otherwise directly identifiable information. Implicit scoring is based on information that the company observes or infers about the prospect, such as their online behaviours (Maria Pergolino, 2015). Another important basic concept about customer scoring is the distinction between Active vs. Latent buying behaviour. The benefits come from adjusting your scoring accordingly. Active buying behaviour identifies “hot” leads based on activities that demonstrate sales readiness and current interest. Latent buying behaviour, on the other hand, involves lower engagement activity. The scoring concept in illustration 5.11 shows sixteen different scoring segments based on purchase frequency and activity level. For each segment, marketer can develop specific programs Illustration 5-10 - Scoring concept (Source: EC4U, Delphine Arvangas)
  41. 41. 41 to bring that particular group of customer to the next segment level. Either up to a higher Recency-Frequency-Monetary score or up to a higher activity level. The principle is to use this scoring model to permanently track customer evolution across the scoring model and propose him the right activation or incentive to develop the relationship positively. Scoring model is essential to develop Marketing Automation programs. The following illustration 5.11 shows another model with five different segmentations based on scoring and their possible actions, focus and benefits. Illustration 5-11 - Media optimization and scoring (Source: Converteo, 2015) Predictive modelling is a commonly used statistical technique to predict future behaviour. Predictive modelling solutions are a form of data-mining technology that work by analysing historical and current data and generating a model to help predict future outcomes. In predictive modelling, data is collected, a statistical model is formulated, predictions are made, and the model is validated (or revised) as additional data becomes available (Pliptop, 2015). Lookalike modelling is an ad tech technics that bring together automation and programmatic buying. It is somehow very near from predictive modelling. It is a
  42. 42. 42 methodology used by marketers to define what users they should target with the highest propensity to buy (Hayter, 2013). They use first party data left over by existing customers to find people who behave in the same way, but who haven not bought a product yet. Let us say an electronic device manufacturer is having a sale and wants to encourage further online purchases. He places a pixel on the sale confirmation page and analyse the behaviour that purchasers have undertaken elsewhere on the web using for example third party data, which are completely anonymous. This group is analysed in order to reveal online behaviours that rank most highly amongst people with a propensity to buy certain products. Analytics and attribution modelling. All the results of a campaign are assessed and measured whether the original objectives have been achieved. Several techniques are used. Modelling is the process of interpreting the campaign results statistically, so that future campaigns can be based on statistical insight into what works and what does not. It is the process of identifying a set of user actions or events that contribute in some manners to a desired outcome assigning a value to each of these events. Marketing attribution provides a level of understanding of what combination of events in what particular order influence individuals to engage in a desired behaviour, typically referred to as a conversion. Often, the attribution of the sale is given to the last touch point, e.g the website (last click wins model). The most attribution modelling used in the practice are the “U model” where the first and last interaction are over proportionally valued. Some other model are: the “progressive model” where each click receive an increase value, the “linear model” where all interactions are valued at same level, the “digressive model” where each interaction loose value with time (Fétique, 2015). Reporting. The campaign results are computed and delivered in standard or customized management reports to relevant parties. 5.6.6 Activation Once the data is processed, Data Management Platforms can suggest segments that may be activated. There are three major activation possibilities shown in the illustration 5.9. Paid media covers all paid advertising medium such as display banners, search,
  43. 43. 43 mobile and social units for example. Depending on the analysed data, the campaign management system will activate a campaign using one or the other paid medium. The second category is owned media, which covers email, mobile or website. Owned media is a channel a company control. There is fully owned media like a website and partially owned media like Facebook fan page or Twitter account. Often, owned media are activated in combination with personalization. This means a newsletter or a website- landing page will be personalized with the user preference and based on its past purchase or behavioural history, pre-analysed in the data management platform. Finally, offline medium may also be activated through call centre, in store communication or why not printed direct mailing. 5.6.7 Application example For a concrete application of Marketing Automation flows, we have structured the exemplary rules following the principle of the customer life cycle represented in the illustration below, which is another view of the “Enhanced New Marketing Automation Model” introduced in chapter 5.3. The main difference lays in the fact that the illustration shows the specific activities the company could activate for each stage of the customer life cycle. As opposed to mass media activities, the advantage of Marketing Automation is its ability to identify micros opportunities to engage with small amounts of prospects or customers. The interest lays in the succession of marketing rules that can be designed in advance and that are automatically triggered when a particular customer event occurs. The charts conceptually show the major key opportunities to engage with a prospect or customer at different stage of the customer life. We have selected six key different phases. Each of them describes a particular moment of the customer life cycle, which deserves some specific engagement tactics. The table 5.12 below is an attempt to describe the above Marketing Automation flows for each of the mentioned phases from 1 to 6. As seen in the chapter Marketing Automation Rules 5.6.2, the rules are composed of triggers, conditions, timing, and activations. To make the rule more real, we have added a communication message. We also have mentioned the main technology or functionality used to execute the rule.
  44. 44. 44 Illustration 5-12 - The 6 steps of the customer life cycle
  45. 45. Illustration 5-13 - Examples of Marketing Automation flows # Life Cycle Event Condition Timing Activation Message Main used technology 1 Capture The prospect is visiting the company website He is browsing the company site for > 3 minutes and belongs to the hot lead segment 3 minutes Newsletter sign up form is automatically displayed as a pop-up message Invitation to receive a newsletter with incentive User progressive profiling 2 Nurture The prospect signs-up the company newsletter (or create an account) The prospect isnt' a customer Nurturing program over 6 weeks Newsletter introductory offers Welcome program of 5 email messages presenting interesting facts about the company Nurturing 3 Remarketing A prospect is visiting a particular webpage 3 times consecutively withing the same week The prospect has left the webiste without ordering Realtime Display or serach remarketing campaign is launched Promotion Remarketing 4 First Sell The propsect's session is unsusuall long lasting > 5 minutes The prospect isnt' yet a customer 5 minutes A web chat is launched The customer agent is proposing some help Customer support 5 Build Advocacy A customer has birthday soon The custome is a top customer 10 days ahead The prospect receives a discout promo-code as a birthday gift Happy birthday. Celebrate with us. Scoring 6 Re-assess A customer has not ordered since 12 months The customer is part of the top customer segment After 12 months A special promotion is sent per email Long time no see? here is a special gift for you if you order Scoring
  46. 46. 5.6.8 Summary With the introduction of marketing automation, we have shown the growing importance of the discipline across the late 1990 influenced by the change in customers’ behaviour on the Internet, the 2008 crisis and the raise of the cloud computing (see chapter 5.1). Marketing Automation is not exclusively used by sales people anymore but by a growing number of business to consumer companies and marketing teams essentially to manager their huge volume of customer interactions in a more efficient manners. The Marketing Automation industry is however quite small with only about 10% of the larger companies which are are using it, and about 3% of small companies. We have also selected most representative Marketing Automation definitions and tried to give the reader the most precise definition. We have kept the following lead definition in mind while writing the thesis: Marketing Automation is a category of technology that allows companies to streamline, automate, and measure marketing tasks and workflows, so they can increase operational efficiency and grow revenue faster (Jon Miller, 2013). Beyond that, we have introduced forms of business automation such as sales automation, service automation and Advertising Automation (see chapter 5.3 and 5.4) in order to give the reader the most comprehensive view of the discipline. Finally, we have proposed the “Enhanced New Marketing Automation Model” presented in chapter 5.6 which was designed based on the following existing marketing automation model: the Forester model (see chapter 5.5.1), the Heimbach Model (5.5.2) and the Carter’s model (5.5.3). Our newly enhanced model is highlighting two major key component of Marketing Automation: The Data Management Platform and the Campaign Management System which we hope gives the reader a better understanding of its core functional scope. The following chapter will be taking the reader across the research questions that we have designed based on the “Enhanced New Marketing Automation model” in mind and used for the interview of the qualitative content analysis.
  47. 47. 47 6 Research 6.1 Study design The figure below shows the study design used to write this paper. The study design is divided into three main phases. The first phase refers to the desk research and the second phase refers to the qualitative research study. The third to the objectives of the research, in particular it show the question that the content research analysis has answer. We discuss the study design more in details in the following sub-chapters: Illustration 6-1 - Study design for qualitative content research 6.1.1 Desk research In order to gain a greater understanding of the research field and to build a base for the qualitative research, the current state of research has been explored. The extracted information forms the base for the qualitative research study.
  48. 48. 48 6.1.2 Qualitative Content Analysis For the qualitative content research (QCA), a study semi-structured expert interview has been chosen as the main method. According to Schreier (Schreier, 2012), qualitative content analysis is a method for systematically describing the meaning of qualitative material. It is done by classifying material as instances of the categories of a coding frame. For our qualitative research, we have organized the work around these 10 steps (Leicester, 2015).  Deciding on you’re a research question  Selecting the material  Copy and read the transcript - make brief notes in the margin when interesting or relevant information is found.  Go through the notes made in the margins and list the different types of information found  Read through the list and categorize each item in a way that offers a description of what it is about.  Identify whether or not the categories can be linked any way and list them as major categories (or themes) and / or minor categories (or themes).  Repeat the first five stages again for each transcript.  When we have done the above with all of the transcripts, collect all of the categories or themes and examine each in detail and consider if it fits and its relevance.  Review all of the categories and ascertain whether some categories can be merged or if some need to them be sub-categorized  Finally the interpreting and presenting of findings. Based on the research question and the literature research, an interview guide has been written which can be found in appendix 7.1. The interview guide is characterized by open questions, which allows and encourages personal answers to be given by the interviewees (Mayer, 2013). We have taken notes during interviews (transcribing) or observations and take a recording so that we can concentrate and listen and respond better. Due to data protection of the interviewed companies, some recordings are
  49. 49. 49 treated confidentially. The transcriptions have been sent to each of the interviewees for validation and can be found in appendices 7.1. 6.1.3 The researched questions The objective of the thesis is to answer the below questions designed around the development of the “Enhanced New Marketing Automation Model”, presented earlier in chapter 5.6, the lead question being: “What are the required means, skills, tools and processes for successful Marketing Automation, leading to marketing efficiency and more revenue generation?”  Research question 1: What are the main reasons for implementing Marketing Automation and the benefits? (see findings in chapter 6.2.1):  Research Question 2: What information and technology infrastructure is required for successful Marketing Automation operations? (see findings in chapter 6.2.2)  Research Question 3: How is the data stored and processed (analysed, structured)? From what sources? (see findings in chapter 6.2.3)  Research Question 4: Who is in charge / organizational chart / sponsor for Marketing Automation? (see findings in chapter 6.2.4)  Research Question 5: What are the most efficient Marketing Automation rules or flows? (see findings in chapter 6.2.5)  Research Question 6: What are the success factors for operating Marketing Automation? (see findings in chapter 6.2.6)  Research Question 7: What are the challenges and obstacles when implementing Marketing Automation strategies? (see findings in chapter 6.2.7)  Research Question 8: What do you believe is up next for Marketing Automation? (see findings in chapter 6.2.8) 6.1.4 Sampling Part of the data used in this paper will been collected in performing interviews with experts in automation in various industries. The principle is to represent diversity so that
  50. 50. 50 broad material of data can be captured from the interviewed professionals. Online retailers are in general more interested in Marketing Automation than companies without an online shop (Heimbach, 2015), therefore the focus was primarily companies with e-commerce capabilities. The interviewers were selected based on their experience of the topic and readiness to participate the survey. The questionnaire used for the qualitative content research was designed according to the “Enhanced New Marketing Automation Model” proposed in the chapter 5.6. The aim of the interview is to meet various business-to-consumers (B2C) and business-to-business (B2B) companies’ professionals using Marketing Automation across industries of different sizes and countries such as CRM, Retail e-commerce or marketing departments. Illustration 6-2 – 12 interviewers’ sample list
  51. 51. 51 As the illustration 6.2 shows above, three companies are in Business to Business and nine companies are qualified as Business to Consumers. One interview was conducted with Marketing Automation consulting agency and one with a software editor. 6.2 Research findings In this chapter we have used the content of all the twelve interviews and structured the respondent’s answerers around our research questions and the coding used for the qualitative content analysis. Detailed coded interviews can be found in appendix 1.1. 6.2.1 The root causes and benefits for implementing Marketing Automation In this chapter, we have grouped all most cited reasons for implementing Marketing Automation. Here was the researched question: “What root cause made you implementing Marketing Automation and to answer what business question? For what benefit?” We found out the following reasons that we have structured by topics: Marketing Automation should be considered as fundamental component of any customer centric strategy. It is most suitable for companies with large volume of customer interactions across complex digital customer journeys and to improve marketing efficiency processes. Increasing customer satisfaction, increasing incremental sales to avoid storing data in silos was systematically quoted. “The idea behind Marketing Automation is the marketing orchestration, in other words to combine all communication channels in a consistent framework, so that you can interact in a consistent way and really accompany your customers across channels with a consistent message and at the end of the day this will be generating revenue (Interviewee_1, 2016)”. The customer journey being extremely complex today, it is important to be able to offer the customer a unified and consistent shopping experience across medium. For multichannel merchants, preferring online or offline is not the question but offering both online and offline channels in one unified experience is the most important aspect. At the end, the objective is the personalization of advertising and content. The right
  52. 52. 52 message to the right customer at the right moment in the right context is at the end the objective. Integration with sales is important for many of the respondents as well. Making sales team happy in providing qualified traffic is certainly a fundamental motivation for Marketing Automation operators, especially in the Business to Business area. “A reason for implementing the Marketing Automation was the integration with the sales CRM and sales force tool in order to manage and automatize more. So every day we can send the top leads to our sales departments and they can see how hot they are. That is a really great function that sales team really love because you are basically not shooting them in the dark (Interviewee_9, 2016)”. Data management and particularly the data quality management was mentioned as a critical issue that should be taken as a strategic business question. The opportunity to get first hand customer information or first party data was named as a key advantage, even if data privacy is a growing concern. “The customer data storage might be threaten by the legislator in the future, to protect data privacy more. The change in the safe harbour laws is a concrete signal for it (Interviewee_9, 2016)”. High efficiency and measurability of the marketing campaign is a key decision factor for implementing Marketing Automation, in particular the ease of measuring digital return on investment and understand what prospect of customer do. Company wants to be capable to save money and resources by automating repetitive tasks in order to reallocate money to most successful marketing campaigns. The repurchase rate was quoted as important KPI to measure success, especially when merchant are operating in the retail e-commerce business and need their website to be generating traffic or when the buying process is particularly long. Companies are searching to improve the ease of managing complexity such as multiple layers of co-existing automated flows involving several thousand of contact. They want to diminish the risks of errors. “At the end, Marketing Automation tries to capture customers data into one system and set up an infrastructure to track behaviour and send them some communication without doing too much manual work” (Interviewee_9,
  53. 53. 53 2016). “There are company that are launching several products, several lines in several countries with limited resources and the only solution is to automate things” (Interviewee_8, 2016). Merchants also wants to educate customers to complex products or services which need on-going education. “A TV 20 sec copy isn’t the appropriate medium for educating customer about a product as opposed to a nurturing program, which can be activated in a more appropriate manner and in a more detailed way (Interviewee_12, 2016)”. 6.2.2 System architecture Since Marketing Automation essentially relies on technology, we thought we would put together information about technical architecture recommended for Marketing Automation. Our researched question was: “What information and technology infrastructure is required for successful Marketing Automation operations?” This what we found out: Most interviewee agree to say that the primarily role of Marketing Automation is to do the marketing campaign orchestration. “The CRM will be managing the customer records and sales, the data warehouse will be the place where you will be doing your data analysis, the data discovery, and consolidate data from different channels (Interviewee_1, 2016)”. To have a solid customer referential is another very important aspect. This can be a CRM, a data warehouse or even the e-commerce itself. The system architecture should be divided in three layers: first the data layer on the down side, which is relying on the Data Management Platform. Data management platform is used essentially to reconcile different sources of data and for advertising in order to get the most qualified placement. Data Management Platform is part of the automation tool suite. It consolidates external and internal data such as first, second and third party data. The orchestration layer would be the second layer which is the place where the business people design more sophisticated campaigns and manage channels, timing, conditions and messages to customers. Marketing Automation can offer value at every single steps of the customer life cycle, consolidating new consumer data, building the relationship with existing customers, re-engaging lapsing customers, reengaging dormant or
  54. 54. 54 removing unprofitable customers. Finally, the third layer is more a customer communication layer or the visible part for the prospect such as website, CMS, e- commerce, mobile etc. Some tools such as Maximizer1 allow the merchant to personalize the content based on the scoring model. Finally, interviewees draws our attention to the difficulty to manage big volume of data, leading to possible lower data load performance. 6.2.3 Data Management Marketing Automation works essentially with data. Data is the main asset to make Marketing Automation work. Therefore we have designed the following research question: “How do you store, structure and analyse the data? From what sources?” here is what we found out: The most challenging element is to find the right action for the collected data. “Data collection itself is not the problem; data is available from any source of platform. It makes analytics more efficient, and figure out what action to take is the challenge (Interviewee_5, 2016)”. Here are some possible ideas to help. First it is recommended to choose the right data model that meets the business requirement. This is a key success factor that confirms our recommendation to focus first on the business question seen in the chapter 5.5.2 before starting collecting data. Data model is like mapping guidelines or data dictionary which help to design the database, facilitate its usage and allows to segment or target with more accuracy during the campaign design phase. We have observed that the definition of a customer lead varies from company to company. Therefore the data mapping definition is important before starting the Marketing Automation project. For example, some companies calls a lead a customer question and some other calls it a customer. The data dictionary helps to avoid confusion. One ID for each record should be defined in the data model in order to avoid duplications. A good practice is to use the email address as unique ID. The centralization of the data is another 1 Maximizer: CRM Software: http://www.maximizer.com/
  55. 55. 55 very important success factor in building the data architecture. By centralization, merchants mean connecting different data layer such as Data Management Platform, CRM, Marketing Automation and Data Warehouse. This should help do better marketing because the business owns more data and can get a 360° view of the consumer. It also enables companies to enrich customer profile by putting together first, second and third party data (see chapter 5.6.5) for detailed explanation. “In order to improve the data quality and comprehensiveness, progressive profiling techniques can help companies in getting the data in a non-aggressive way (Interviewee_1, 2016)”. Another innovating method used to enrich first party data used by US interviewees is the integration of third Party data to First party data. The idea is to enrich the company first party data in adding third party data from data brokers. Scoring is a key fundamental which Marketing Automation uses to segment dynamically and in real time the customer base. The scoring is generally based on two or three dimensions such as demographic, purchase history and overall online or offline activity. The recency-frequency-monetary (RFM) method plays a major role in the way managers look at the financial performance of a particular customer. That way, the business could qualify customers in different segments based on the probability that they will buy the product or engage with the brand. At the end, the business wants to be able to rate who are the customers with the highest potential value. Not all interviewees are using scoring methods. Some still use very basic segmentation methods. “In our company we tend to take the whole database and divide it into 2-3 segments for campaigning. E.G Half for male and female with two messages. We always try to reach out 100% of it. Our partners in our sales organization are concerned they would lose opportunities when they address their campaign to too narrow segments (Interviewee_4, 2016)”. 6.2.4 Organization & Processes Marketing Automation is not just technology and a piece of software. Strategy, business questions, processes, resources and people are needed on top to make it work. How exactly? What is the best possible organization and processes to make it function? To answer the question, we have asked interviewees the following question: “Who is in
  56. 56. 56 charge / organizational chart / sponsor for Marketing Automation?” We found out the following: The involvement of the company management is key. The role of the CEO in building the digital customer centric vision is very important. “Finding the right sponsor in the company is the essential challenge, someone that understand the value of Marketing Automation (Interviewee_1, 2016)”. In fact, merchants said to be able to develop Marketing Automation skills with an agency or develop the knowledge internally. At the end, what is important is to be able to build a learning team, to keep themselves informed about the evolution of Marketing Automation, keep up with the pace of change. The software editor is often a critical team member in the sense that it can support the business actively, in both training and consulting. For larger organization, sharing the same Marketing Automation tool across organization and consequently expertise is essential in order to find economy of scales and develop best practices sharing. The collaboration across teams was cited as very important. This is indeed often a very iterative process, which requires a lot of goes and returns, trials and errors until the rule is adopted and works well. Often there is no formal process when it comes to create automation flows or rules, but collaboration across functions and teams is essential. New Marketing Automation opportunity should ideally be identified by business analysts, which carefully analyse the data and make recommendations how to setup the campaigns. “We test a lot thanks to our good project management. We avoid big bangs. We develop in small steps which we can carefully monitor (Interviewee_4, 2016)”. Sometime leadership in in the hands of IT, sometime in marketing or even sales. Teams involved in the Marketing Automation processes are generally structured around several functions such as Digital Marketing (Analytics, social media, SEO experts, webmaster, producers), Branded Marketing (Planning, media, creative, business analyst), IT (Data base engineers, programmers, information architecture, ERP, Data Warehouse) and Sales or Retail (CRM manager, Key account management, Retail manager). In larger international organization, they are mirroring functions at both corporate and local levels.

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