Social Listening: come sfruttare la social intellingence per guidare le data-driven decisions
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Alexi Giorgi e Valeria Severini di Freedata Labs hanno esposto il tema durante il webinair del 9 luglio 2014, illustrando come sia possibile prevedere e indirizzare le decisioni di acquisto grazie a uno scrupoloso uso del social listening. A partire da una richiesta giunta da un cliente, viene analizzato il lancio in Giappone di un prodotto innovativo
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Social Listening: come sfruttare la social intellingence per guidare le data-driven decisions
- 1. pioneers in social media Moving Beyond Social Listening: Using Social Intelligence to Power Data-Driven Decisions in the Enterprise @alex178ita @valesev @freedatalabs VALERIA SEVERINI valeria.severini@freedatalabs.com LONDON, 7 MAY 2014
- 2. SDL partner since 2011 for Italy and EMEA Some of our main Clients are : Ferrari, Prada, Manfrotto, Illva Saronno, Nestlé, Continental, SAP, TNT POST… 2 About Freedata Labs We are a Digital Company, specialised in Social Intelligence and Social Media Marketing Based in Italy and the UK Web site : www.freedatalabs.com SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions
- 3. Client’s Goal After the successful launch in Japan, in April 2013 the client took into consideration the opportunity of launching interactive robots in two European Countries. A Southern Country A Northern Country The Blue Country The Green Country SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 3
- 4. What the client Asked Us Monitoring the Japan launch/campaign In which of the two countries should we launch the product? Which country do we expect to be the most successful? What can be the best digital strategy for each country? SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 4
- 5. Our Response You need a Social Intelligence service! SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 5
- 6. Why a Social Intelligence Service? Social Intelligence Services help us: Understand the key success factors in a new product launch Discover which could be the best story to engage customers Forecast the possible impact of a new product launch SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 6
- 7. The Customer’s Journey SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 7
- 8. Where does the Customer’s Journey Start? An interest in Robotics SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 8
- 9. Visualizing the customer journey landscape SDL Customer Commitment Framework We used the Customer Relevance Score is used to: • Identify the content and messages that inspire engagement and interaction around Robotics • Temperature check on the energy of the community around the robotic product • Identifying the campaign levers that the client can pull to drive engagement • Provide a way to prioritize market opportunity for a publishing product SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 9
- 10. The Customer’s Journey by Country and Channel One keyword Three countries All the web channels SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 10
- 11. The overall robotics landscape in metrics • Highest engagement with the topic of robots/robotics over time • Evidence of slight decline • Only market with an upward trend in the interest • Sustained volume of conversations • No evidence of growth in the online community Customer Relevance Score shows us: Japan has the most vibrant community around robots and robotics so good first entry point Blue, although less active than green has seen interest grow over the last 12 months There is more sharing in the green market but the trend is stagnated SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 11
- 12. Time Series Total Results: Japan SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 12 350 300 250 200 150 100 50 0 2012 2013 Timeframe of the analysis: May 2012 - April 2013
- 13. Total Results: Japan May 2012 - April 2013 Digital Channel % results Mainstream Media 10% Blog 41% Forum 2% Twitter & Ameblo 47% Social Network 0,3% Video/Photo Sharing 0,2% Total 100% 10% 47% 41% % Results .349% 2% .221% Mainstream Media Twitter Blog Social Network Forum Video/Photo Sharing SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 13
- 14. Time Series: the Client & the Robot Pre-Launch Post-Launch SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 14 45 40 35 30 25 20 15 10 5 0 Mainstream Media User Generated Contents
- 15. The overall robotics landscape in metrics – where next? • Only market with an upward trend in the interest • Sustained volume of conversations • No evidence of growth in the online community SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 15
- 16. Visualizing the content relevance journey The Customer Commitment Dashboard allows us to explore how active the robotics community is and which stages of sharing are evident in each market. There are 8 key journey stages: Content Discovery: An individual encounters content on earned, owned or paid media SCORE: Ease of finding relevant content Content Promotion: Active sharing and advocacy of content around subject/brand or product SCORE: Ease of sharing relevant content It starts with discovery and ends with active, vibrant sharing Brands that want to tap into an existing community or market landscape can see exactly where they need to focus to ensure that campaigns will get to the community and will result in sharing / driving earned media SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 16
- 17. Analysing the strength of engagement with Robotics Size of balls = volume of conversations taking place Score = ease of engagement at each stage of the journey Size of balls = volume of conversations taking place Score = ease of engagement at each stage of the journey Blue market has the most vibrant community: Highest volume – c9,300 per month v’s 5,500 per month The ease of sharing across the community is significantly better = all sharing experiences are rated more positively than in the green market SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 17
- 18. Key opportunities to optimise for success in the customer journey CRS: Content Relevance Journey Types • The final stage of the landscape analysis = how to optimize based on the types of experiences customers are seeking SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 18
- 19. Focus for Blue • Self Interested is the dominant journey in the Blue Robotic community • CONTENT OPTIMIZATION REQUIREMENTS: • Easy to consume content across all channels • Analytical focus in materials • Facts, figures and comparisons SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 19
- 20. Focus for Green • Broadcasting is the dominant journey in the Green Robotic community • CAMPAIGN OPTIMIZATION REQUIREMENTS: • Opportunities to share • Social communities to engage through • Ability to show / share activities • Amplification of user generated content SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 20
- 21. What are the main topics of conversations ? SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 21
- 22. Main Topics Across Countries Science: all references to the scientific use of robots such as in surgery, space engineering, other applications. Includes cybernetics and robotics sciences. Commerce: all references to purchase or sales of robot. Home: all references to the domestic applications of robots (kitchen robots, home cleaning robots, etc.) Toys: all references to robots as toys. Movies (and cartoons): all references to films where robots are in the plot. Includes comments about animation movies and cartoons («anime») Books: all references about books talking about robots. Includes comics and manga Military: all results about robots associated to war, weapons, military technology Negative: includes all results with a negative tone about robots, such as negative comments, negative metaphors («cold as a robot»), all texts where the users express fear or hostility towards robots. Pet: all references to robots associated with feelings like tenderness, love, care, pampering, all texts where robots are considered as companion animals SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 22
- 23. Importance of the Topics by Country May 2012 - April 2013 23 Movies/cartoons Toys Commerce Science Negative Military Home Pet Books 25% 20% 15% 10% 5% 0% SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions
- 24. Content Emotions 24 Content Emotion DESCRIPTION ACHIEVE Emotions related to achievement of objectives and personal fulfillment ANGER Expressions representing a mood of anger, hate and violence. The words of the category represent the manifestation of the mood and sometimes its causes as in the case of "enemies" or "punishment" ANXIETY Emotions related to an anxious state of mind caused by fear, anxiety, apprehension BODY Emotions related to elements, characteristics and problems of the human body DEATH Emotions related to the death phenomenon in terms of objects and places connected with the burial, memorial events or death causes. FAMILY Emotions related to family linkages FRIENDS Emotions related to close friendship, business and sentimental relationships between individuals HOME Emotions about the home and the different types of humans and animals habitation INGEST Emotions related to the nutrition field, especially drinking, eating, places and related problems LEISURE Emotions about the use of free time MONEY Emotions about the monetary and financial field RELIGIOUS Emotions related to the worship SADNESS Emotions relating to acts, causes SDL INNOVATE | Using Saoncdi aml aInntiefellsigtaetniocne otfo t Pheo wsaedrn Deassta m-Doroivden Decisions
- 25. 25 Content Emotions by Country 25% 20% 15% 10% 5% 0% SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions
- 26. Segmentation by Talking Style: Big Five Traits, Content Emotions, Topics The linguistic elements of the analyzed texts that allow us to identify the “Content Emotions" are also used to define the “talking style” that characterize of each result. To do this, Freedata Labs leans to the theory of the "Big Five Traits”, which identifies five key factors in the characterization of human social behavior. Using as variables the Big five traits, Content Emotions, and Topics Freedata Labs runs a Correspondence Analysis to define the two main axis underlying the world of Robots. The first axis is: Functionality against Emotionality The second axis is: Separation (the machine’s independence to man) against Fusion (the overlapping of man and machine) Once a Cartesian plane using these two axes has been defined, Freedata labs analyses the relative position of each observed variable for each country. SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 26
- 27. The World of Robots: Four Roles 27 emotionality Books functionality Separation (man-machine) Fusion (man-machine) Commerce Toys Negative Movies Science Home Commerce Negative Toys Movies/cartoons Science Home Commerce Books Negative Toys Science Home Military Robots as… Entertainers Tools Pets Substitutes Emotionality Functionality SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions
- 28. From Segmentation to Influencers SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 28
- 29. Conclusions: Blue or Green ? The Blue country is more likely to be the best country in which to launch the robot. The Blue country showed un upward trend in engagement with Robotics (the CRS Score) and much higher volume of conversations It is focused on science but also on films and books portraying a positive emotional perception of Robots (achieve, leisure). The Digital strategy must be focused on Digital PR along with the engagement of Blogger and Twitter Stars from each relevant segment: Robots as Substitutes (Science), Robots as Pets (Movies and Cartoons) , Robots as Entertainers (Books). Social media sites like Twitter, Facebook and YouTube will support the launch. The existing customer journey we observed means the content strategy needs to focus around facts, figures, comparisons and learning experiences to engage the existing community. Story telling about robots and robotics will drive discovery of the topic and continue to fill the customer funnel SDL INNOVATE | Using Social Intelligence to Power Data-Driven Decisions 29
Notes de l'éditeur
- Thanks Jo and welcome to everyboday also from me and Valeria ...Today we will show you how social intelligence can power data-driven decisions in a project we worked for with De Agostini
- First of all a few words on who Freedata Labs is ....
- Because of its high-demand and the huge success, the company is looking to launche Robi in new markets, possibly Italy, UK, US, France and Spain, Russia .
- SDL’s Customer Commitment Framework (CCF®) enabled us to gain near real time insight from social data. The methodology and measurement framework allows you to listen, analyze and react to customer needs in near real time. It allows you to adopt a data-driven approach to decision making, strategic planning and campaign execution. There are 3 outcomes that the Customer Commitment Dashboard allows you to visualize – the likelihood to buy (PRODUCT COMMITMENT SCORE), Emotional commitment to your brand (THE BRAND COMMITMENT SCORE) and content relevance through the lens of sharing behavior – (CONTENT RELEVANCE SCORE). Customers Relevance Score is the metric on which we focused to assess the overall landscape for Robi the Robot. We needed to understand which markets have an active robotics community and collect robust data to make recommendations on where Robi was likely to be most successful and how the marketing strategy could capture latent interest in robotics. We did this by understanding how active the community is and the key contents that generated conversations.
- Our targets were articles, comments, posts, conversations published ion the web, mentioning «robot» in any possible context for each country or /language. The Customer Commitment Framework ONLY listens to conversations that indicate that someone is on a journey e.g. we only listen to conversations that matter. Using key words that indicate a behavior e.g. whether they are discovering content or already broadcasting content, allowed us to score conversations on a scale of 1 -100. A score of 100 means high propensity to share, highly active and highly influential community. .
- So the overall analysis for the three markets over two years clearly shows that Japan is the ideal first market. There is a well established, active community and interest and engagement with Robotics is high (CRS scores in approx 70).
- The conversations around Robots have no significant trend, although there is a clear peak in decemeber of 2012, when Robi the Robot was launched and another, lower, high-point in May of 2012 during the Fukushima emergency. In general the average number of conversation is of 100 results per day.
- The main digital channel in Japan is Microblog, including Twitter , Ameblo and Blogs. These are the places where influencers of the Robot enjoy discussing and sharing posts, ideas, images and their passion and emotions around Robots. So Robots in Japan is a very talkable subject.
- The launch has been supported by Digital Pr activities on mainstream media, but a relevant buzz on users generated content amplified the effect. As you can see the share of voice of Robi the Robot inside the world of robots growths quickly especially in the user generated contents.
- But the key question for De Agostini was: where next? So we used the Customer Commitment Dashboard to dive more deeply into the landscape. If you remember – we saw in a previous slide that the for the Blue market, although a little lower in overall engagement with the robotics subject was showing a steady upward trend in interest. The next level of analysis we did was looking at the sharing journey end to end.
- There are 8 stages on the sharing journey defined by CCD. Once again, we used keywords to indicate if someone is at a specific stage of the journey, this means that when posting on a subject you use different terms if you are just discovering a new topic rather than you are an expert and confident to broadcast what you know and think. So the journey starts with discovery, move through a series of phases where people are more deeply connected to the subject and eventually are projected into an influential and active participation in the community. We used this to identify where we have the most clear opportunities and to guide our messaging strategy.
- So when you visualize the customer journey for the Blue and Green markets. Blue market has the most vibrant community: Highest volume – approx 9,300 per month compared to 5,500 per month The ease of sharing across the community is significantly better = all sharing experiences are rated more positively than in the green market So on the surface it looks like the Blue market would be the easiest to enter. The next stage of the data driven analysis was to look at how to optimize the content and messaging for the different markets.
- The Customer Commitment Dashboard help you to prioritize marketing activity based on the main types of content consumptions that is going on in the market. For the Content Relevance Score, there are 4 journey types – Exploration – about discovery & intrigue, Magnetism – about capturing people with the WOW factor. Self interested – about understanding, analyzing and being confident in what you know Broadcasting – all about enabling people to share, show off their knowledge and drive the conversation So what did the Blue and Green Markets looked like?
- The Blue market was dominated by the ‘Self-Interested’ journey – the community wants facts, figures, experiences and access to knowledge. It shows that the community is the middle of the journey – mainly focused on education – a great opportunity for De Agostini.
- The Green market is all about broadcasting your knowledge. What do you know, what you can you share. Successful marketing needs to be socially driven and about building and supporting the EXISTING community to maximize opportunities. As many of you that have to build social communities and strategy know – it takes time and investments. On balance – we felt that the opportunity looks greater and potentially simpler in the Blue market. But this was the beginning of our analysis – we now had a robust data view of the potential markets – now it was time for us to go deeper into the underlying conversations and work out how to best tackle the opportunity through a content strategy.
- Through an in depth analysis of the texts, we identified nine main «Topics». Using appropriate keywords, all results have been automatically assigned to one or more topics (some texts could not be associated to a specific issue). The Topics, valid in all the three countries, are:
- In Japan the ooncept of Robot is associated with entertainment , movies , cartoons , books, toys and pets. All subjects which are easy to talk about . In The Blue Country science is the most important topic followed by movies and cartoons; books and toys are not relevant. The Green Country is very different since all the topics have almost the same relevance, so none of the topics is really important. Conversation on robot are connected with military environments, with home machine and scientific discussion, so it seems to appear a very functional way to talk abour robot.
- To enrich the quantitative analysis of the extracted web results, we associated with each text one or more «emotions»: the content emotions are defined using predefined dictionaries defined by psycometrics specialists. Using these special dictionaries, all the texts analyzed were associated with one (or more) "basic emotions", to characterize the tone of the conversation and provide useful information. The incidence of the various emotions provides a general picture of the feelings of the users when talking about the analyzed subject.
- In the Japanese web the main emotion is associated with Body (arms, legs, head). Second in rank is Leisure. In the Blue Country we see two main emotions associated with the conversations about robots: Leisure and Achievement And in the Green Country, In addition to the Body emotion (same as in Japan), we see a different association: Anger (and violence), much more relevant here than Leisure or Technical Achievement. So we have tre different emotional profile emerging for each country
- The two dimensions define four roles : first Robots as entertainer, Robots as Pets, Robots as tools and Robot as Substitutes. In Japan the world of robots is deeply present in the cultural background and therefore widely discussed, interpreted, developed, felt and lived without prejudices. From science to manga, from pets to home appliances, robots are present in everyday life and are as common and natural in the Japanese vision as food is in Italy. In Blue Country the imaginary about robots is quite clearly polarized across the linear contrast of emotion and function, without ever living fully the roles of robots as entertainer, pet, tool, useful substitute. Movies, Books, Toys and Negative are the more emotionally charged topics. In The Green Country the culture of robots is definitely functional: the emotional/affective component is not discussed. People talk about robots with rationality, and in a very «cold» way, ranging from science, treated almost like a curiosity issue for amusement and short readings, to toys, approached almost as a scientific discipline.
- The digital Pr and influencers engagement activity starts from ranking top domains and influencers by segment. Segmentation is an optimization procedure to maximize the engagement results with a predefined number of influencers.