Addressing Today’s B2B Tech Marketing Challenges
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We take a look at how today’s most successful B2B tech marketers are leveraging data to identify their addressable market and influence active researchers. Since not all data – and therefore not all data providers – offer the same value, Kevin offers insights on what to look for when investing in pre-purchase data. He then shows you how reliable data can accelerate your ROI from a variety of marketing activities including lead generation, automated nurture, account-based marketing and targeted brand-building initiatives.
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Addressing Today’s B2B Tech Marketing Challenges
- 1. ©TechTarget 1 Addressing B2B Tech Marketer Challenges Kevin Beam President October 2017
- 2. ©TechTarget 2 What marketers tell us their focus is Marketing automation & scoring Account-based marketing Intent data & predictive MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Challenges Response How TechTarget Can Help
- 3. ©TechTarget 3 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Marketing automation isn’t magic; it takes a lot of work and a lot of content • Nurture steams need to be conceived, created and customized • These systems still aren’t always graduating the best leads to sales Marketing automation (lead scoring & nurturing) Challenges Response How TechTarget Can Help
- 4. ©TechTarget 4 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Diving into the issues: the state of affairs Current state Generally don’t factor in account-level, predictive or purchase intent insights Engagement based scoring isn’t panning out (not enough MQLs generated) Many scoring models are partly profile-based (titles, company size) Sales is dissatisfied because the proper expectations may not have been set Effective sales follow up is a problem due to inappropriate SLAs Impact or issue False negatives and positives enter into the equation (see below) False negatives: Prospects aren’t progressing through 4-5 touch models False positives: Based upon assumptions or ideals not reverse-engineered from real deals The effect of nurturing and scoring on lead volume and quality are not well understood If a lead is deemed to be qualified it’s important to change the disposition methodology Challenges Response How TechTarget Can Help
- 5. ©TechTarget 5 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE A note on false positives and false negatives Courtesy of Kerry Cunningham, SiriusDecisions What you think? Reality Correct No False Negative False Positive Correct Yes False True False True Goal: Avoid both the False Positives and False Negatives False Negatives mean that you are missing out on a portion of the active demand for your solutions False Positives waste resources and effort and can hurt Marketing’s credibility with sales Challenges Response How TechTarget Can Help
- 6. ©TechTarget 6 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE A brief note on BDR/SDRs What leads do they think are the best? How do they know which leads are good? What is their role in this process? Today’s So what happens to yesterday’s? “They take my call or call me back” “They take a meeting or acknowledge a planned purchase” • Identify • Qualify • Engage Challenges Response How TechTarget Can Help
- 7. ©TechTarget 7 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Implement simpler and more compressed nurture streams Drip is too slow; use “modules” designed to engage Use your best content across multiple streams Enable binge content consumption/self-nuture New scoring models What we see in terms of best practices Challenges Response How TechTarget Can Help
- 8. ©TechTarget 8 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Set sales expectations and agree upon SLAs at the outset Deploy new lead disposition models 30 appointments in the next 2 weeks 72 hours to penetrate as many accounts as possible Pay on pipeline versus activity metrics What we see in terms of best practices Challenges Response How TechTarget Can Help
- 9. ©TechTarget 9 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE * Source: SearchMetrics Marketer KPIs Brand lift Demand gen quality & velocity MQL/SQL conversion Strategic plays Inbound marketing (SEO/SEM) ABM & persona marketing Lead nurturing & scoring Marketing analytics/ data modeling Business goals New customer acquisition/market share Customer retention/experience Sales and marketing productivity Search #1 in B2B tech Search* 800K+ first page results on Google Captured intent Content Web’s largest collection of purchase-focused B2B IT content 275K+ original expert- written articles Audience 150M unique annual IT and LoB visitors 100K weekly active accounts with buyer-supplied data Data applications Priority Engine™ Qualified Sales Opportunities™ Deal Data™ Buyer Research Activity #1 source of intent activity across 5,000 IT segments All accounts and prospects re-ranked weekly Marketing programs Branding Demand gen Integrated Challenges Response How TechTarget Can Help
- 10. ©TechTarget 10 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Through Priority Engine: • Stack rank any existing leads or accounts in your database • Get advice from our Client Consulting team on how to use this for scoring • See which of your TechTarget leads are most active and who else is researching at those accounts • Pass along account-level insights • Use TechTarget media formats that enable self-nurture Marketing automation & scoring using Priority Engine™ Challenges Response How TechTarget Can Help
- 11. ©TechTarget 11 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Treating each account as “a market of one” is a great way to get your head around the concept of ABM, but how do you scale that? • ABM changes KPIs for marketing • It’s important to deliver not just inroads (leads) but insights (so sales can execute their plays) • The marketing-to-sales handoff is not engineered for ABM ABM Challenges Response How TechTarget Can Help
- 12. ©TechTarget 12 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE 3. Build insights2. Identify contacts 4. Create messaging 5. Drive interactions 6. Execute plays 1. Define accounts Steps to building an ABM strategy Challenges Response How TechTarget Can Help
- 13. ©TechTarget 13 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Challenges: • Efficacy versus effort: Consider whether your selection is truly based upon propensity to spend and fit versus profile and aspiration ⎻ Priority often beats purity: Where can I win vs. where do I want to win? • The size of your list should be in synch with your activation plans • Go as far as you can to define the actual buying unit Define accounts Build insights Identify contacts Create messaging Drive interactions Execute plays Define accounts Challenges Response How TechTarget Can Help
- 14. ©TechTarget 14 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Are you going for entry points or engagement? • Productive ⎻ Sourcing details on the right personas or identifying engaged buyers • Potentially counterproductive ⎻ Simply maximizing leads or number of names lead to false positives for sales and spam issues for marketing Identify contacts Build insights Identify contacts Create messaging Drive interactions Execute plays Define accounts Challenges Response How TechTarget Can Help
- 15. ©TechTarget 15 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • This can be sales work or marketing but the sales work cannot be done at scale • Some predictive providers or compiled data providers can help • Insights can be improved with purchase intent behavior • Low hanging fruit is commonality (don’t underestimate this) Build insights Build insights Create messaging Drive interactions Execute plays Define accounts Identify contacts Challenges Response How TechTarget Can Help
- 16. ©TechTarget 16 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Except for ultra-customized small-list ABM efforts, this is about verticalizing your content and messaging or capitalizing on other common themes ⎻ You don’t have to break the budget ⎻ Case studies are half the battle ⎻ Get help from sales • Once you’ve identified your messaging segments, mine your own lead data for content consumption patterns that surface more themes Create messaging Create messaging Drive interactions Execute plays Define accounts Identify contacts Build insights Challenges Response How TechTarget Can Help
- 17. ©TechTarget 17 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Be wary of traditional front-end KPIs • The most successful customers focus on: ⎻ Inroads: Get this to an overall level of engagement at the account that sales can leverage ⎻ Insights: Pay attention to how and with what they engage • Pass this along to inform sales plays Drive interactions Create messaging Drive interactions Execute plays Define accounts Identify contacts Build insights Challenges Response How TechTarget Can Help
- 18. ©TechTarget 18 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • The hand-off to sales can be a challenge o Not well supported by traditional MarTech and CRM • Key is ability to pass along account insights o Enable ABM in Marketo o ABM-specific solutions like Engagio • Or being able to manage the follow-up cadence and lead disposition differently o Opportunity object in Salesforce (zero dollar) o Tools like Sales Loft Execute plays Create messaging Execute plays Define accounts Identify contacts Build insights Drive interactions Challenges Response How TechTarget Can Help
- 19. ©TechTarget 19 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE 1. Define accounts Priority Engine can help identify in-market accounts that fit your profile and help you develop, maintain and refresh your list Revisiting this: How Priority Engine helps build an ABM strategy Challenges Response How TechTarget Can Help
- 20. ©TechTarget 20 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Account-based marketing Build insights Identify contacts Create messaging Drive interactions Execute plays Define accounts How TechTarget Can Help: • Identify the most active accounts that buy what you sell • Prioritize your target accounts and identify the active purchase researchers • Identify other active accounts that look like your targets • Target those accounts with content marketing Easy Marketing Hard Marketing In-Market Accounts ABM Accounts Challenges Response How TechTarget Can Help
- 21. ©TechTarget 21 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE 3. Build insights Our data and reporting tools can help you develop an account level view of engagement to measure your results 2. Identify contacts Priority Engine provides not only which accounts are in- market but actual individuals doing purchase research plus key buying personas 4. Create messaging Our client consulting team can provide you with backend data on account, segment and market personas that inform messaging 1. Define accounts Priority Engine can help identify in-market accounts that fit your profile and help you develop, maintain and refresh your list Revisiting this: How Priority Engine helps build an ABM strategy Challenges Response How TechTarget Can Help
- 22. ©TechTarget 22 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE What buyers are telling us about their next enterprise systems management tools purchase Drive interactions Execute plays Define accounts Identify contacts Top Drivers Top Features Top vendors being considered for purchase 1% 7% 10% 10% 13% 17% 17% 17% 19% 20% 20% 26% 28% 58% Kaseya Symantec ManageEngine Oracle CiscoWorks CA Technologies Dell EMC (incl. Kace and… IBM HPE ServiceNow SolarWinds BMC Software VMware Microsoft 44% Achieve better control over IT lifecycles 38% Improve IT cost-efficiency 33% Automate routine tasks 60% IT inventory and asset management 57% System performance monitoring 41% Configuration management (CMDB) Create messaging Build insights Challenges Response How TechTarget Can Help
- 23. ©TechTarget 23 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE 3. Build insights Our data and reporting tools can help you develop an account level view of engagement to measure your results 2. Identify contacts Priority Engine provides not only which accounts are in- market but actual individuals doing purchase research plus key buying personas 4. Create messaging Our client consulting team can provide you with backend data on account, segment and market personas that inform messaging 5. Drive interactions We can promote to active researchers on your target account list; we can drive pipeline from active accounts outside your list 6. Execute plays Priority Engine embeds account-level insights. Qualified Sales Opportunities provide detailed sales plays. Perfect for land & expand 1. Define accounts Priority Engine can help identify in-market accounts that fit your profile and help you develop, maintain and refresh your list Revisiting this: How Priority Engine helps build an ABM strategy Challenges Response How TechTarget Can Help
- 24. ©TechTarget 24 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Challenges Integrating the data with current systems, process and activities Obtaining Actionable insights and inputs from your efforts that can drive marketing outcomes Identifying real purchase potential (eliminating false negatives and positives) Challenges Response How TechTarget Can Help
- 25. ©TechTarget 25 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Hierarchy of data types • Account level insights are key • The fastest path to a return comes from combining data sources • Not all intent data is created equal Account assessment Data type Based upon Helps with understanding… Profile Compiled What you know (or what everyone knows) What’s possible Potential Predictive (internal) What you can learn from internal data Fit for your solutions Propensity Predictive (external) What you can learn from external data State/readiness Probability Intent (internal) What behavior you capture in your systems Interest Priority Intent (external) What behavior can be captured on the Web Intensity Challenges Response How TechTarget Can Help
- 26. ©TechTarget 26 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Obtaining actionable insights: Partial data may not be actionable It is still challenging to identify and engage the most likely buyers, both inside and outside of your own ecosystem • It makes sense to build productive profiles for lookalike targeting and scan for possible signals of intent • But application and implementation can be complex and reliant upon guesswork WHO? WHAT? WHEN? Most of the time, you only know one or twoof these things at best Challenges Response How TechTarget Can Help
- 27. ©TechTarget 27 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Obtaining actionable insights: Most providers tell only part of the story Intent Insights (Data Inputs) Predictive Platforms (Data “Organization”) Marketing/Sales Overlays (Applied Data) • Accounts only • Hypothesis methodology • Shallow info • Based on your historical signals • Account-based view; lacking new named prospects & activity • Org structures & contacts but no sense project interest/involvement • Limited permissions • TOFU (programmatic) WHO? WHAT? WHEN? WHO? WHAT? WHEN?WHO? WHAT? WHEN? [Programmatic/DMP] Challenges Response How TechTarget Can Help
- 28. ©TechTarget 28 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE Success in B2B starts with accurate insight into purchase intent It all comes down to rank and relevancy Content Focus Identifying real purchase potential: Not all intent data is created equal Challenges Response How TechTarget Can Help
- 29. ©TechTarget 29 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Predictive and intent-based initiatives are by their nature account-based • Accounts, leads or opportunities identified through predictive methodologies or external intent signals require campaign- based follow-up • The priority is to ENGAGE Integrating with your systems and efforts Challenges Response How TechTarget Can Help
- 30. ©TechTarget 30 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE TechTarget has more top ranking search results than any other B2B technology publisher worldwide Source: SEMRush. Includes ALL regions reported as of 12-1-16. Includes only B2B tech sites published by these resources Number of organic (non-paid) keyword rankings in Google’s top 10 Monthly cost if you were to buy the organically driven traffic 26K 26K 40K 45K 107K 243K 274K 537K 809K Gartner 1105 Tech Media UBM Tech The Register Spiceworks Quinnstreet Enterprise CBSi IDG Enterprise TechTarget $0.4 $1.2M $1.5M $1.6M $2.2M $3.4M $9.2M $11.5M $38.5M 1105 Tech Media The Register UBM Tech Spiceworks Gartner CBSi Quinnstreet Enterprise IDG Enterprise TechTarget Numbers in thousands Numbers in millions except for 1105 Tech Media Challenges Response How TechTarget Can Help
- 31. ©TechTarget 31 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE How better external intent data is made and made available Your audience: Deep content footprint and Search dominance: 140 B2B Tech Web sites; 550K+ indexed content pages, 800K first- page organic Google rankings Strong signals: Buyer research details tracked on individual buyer level, yielding visibility into purchase intent in specific market segments Easy access: Priority Engine™ is the central warehouse for all this account and prospect activity intelligence Qualified Sales Opportunities™ are individual account reports of an in-process purchase decision 75K content items produced annually 200M inbound visits from organic Search 1M daily buyer interactions across 10K topics 100K accts per month; 18M registered members Challenges Response How TechTarget Can Help
- 32. ©TechTarget 32 MARKETING AUTOMATION & SCORING ACCOUNT-BASED MARKETING INTENT DATA & PREDICTIVE • Stack-ranks accounts and provides contact info for actual researchers • Insights on topics, vendors researched • Turnkey integration with existing systems and processes • Can be foundation for your strategy or enhance your existing efforts Priority Engine Challenges Response How TechTarget Can Help
- 33. ©TechTarget 33 What marketers tell us their focus is Content development Fueling pipeline Marketing automation & scoring Account-based marketing Intent data & predictive
- 34. ©TechTarget 34 • Engage us whenever you need fuel for your efforts • Engage us early so we can help you set strategy and support key initiatives • We can show you who needs your solutions, what they care about, when to contact them and how best to communicate TechTarget Strategic partner and execution partner
- 35. ©TechTarget 35 Thank you. Kevin Beam President
Notes de l'éditeur
- Adapt your scoring model Score off of late stage consumption, length or intensity of engagement Factor ABM principles and purchase intent signals into scoring
- Set sales expectations and agree upon SLAs at the outset Sales understand they will see fewer high quality leads We’re seeing new models for disposition 30 appointments in the next 2 weeks 72 hours to penetrate as many accounts as you can on this list Pay on pipeline versus productivity metrics
- Treating each account as “a market of one” is a great way to get your head around the concept of ABM, but how do you scale that? ABM completely changes KPIs for marketing It’s not about he number of contacts It’s about the right contacts, account penetration and engagement You can’t just change strategies and targets, you must change tactics and measurement You need to deliver not just inroads (leads) but insights (so sales can execute their plays) The marketing-to-sales handoff is not engineered for ABM Scoring models, systems & processes, SLAs, and follow up strategies need to change
- Efficacy versus effort: Consider whether your selection is truly based upon propensity and probable spend and fit versus profile and aspiration Be careful what your missing based upon your limited perspective Predictive and Intent models can help Prioritization sometimes beats purity (where *can* I win?) The size of you list must fit your activation plans It’s all about personalization but you need to find common themes and traits to scale Go as far as you can to define the actual buying unit At least regionalize… Ideally define discrete divisions and teams Sales can help Otherwise it is hard for you to action and you will have sales handoff problems
- Consider your objectives The issue people run into here is mixing this step up with step 5 (engagement or lead-gen phase) Are you going for entry points or engagement Are you sourcing for marketing or for sales? Productive: Identifying and sourcing contact details on the right personas Identifying engaged buyers Potentially counterproductive Simply maximizing lead-count or the number of names Potential false positives for sales Potential spam issues for marketing
- This can be sales work or marketing but the sales work cannot be done at scale Some predictive providers (and list providers can help) Take it for what it is, profile information versus intent The best insights can come from purchase intent behavior What you can discern from content consumption Augmented by outside sources This is critical to the long game (because it gives you hooks to engage based on interests and behavior versus just situation) and maximizing your opportunity (because it identifies priority accounts) Low hanging fruit is commonality (don’t underestimate that) Themes or traits you can leverage for campaigns or sales plays Allows you to play games you know (key purchase drivers, verticals, competition)
- Except for ultra-customized small-list ABM efforts, this is about verticalizing your content and messaging or capitalizing on other common themes It doesn’t have to mean crazy content budgets You can accomplish a lot with messaging and just customizing the front-end of your assets Case studies kill: Use your case studies like a microsite Link to other content Consider interactive formats Use parts of your case studies as a wrapper or callouts in other assets. Here, sales can help a lot (tap into their customers most common complaints) This beats elaborate research and data analysis Once you’ve identified your messaging segments, mine your own lead data for content consumption patterns that surface more themes
- We see a lot of issues here People set aside best-laid plans and focus on now many leads or names they can generate You get compelling front-end KPIs but your prospect gets spammed Your actual ABM conversion may be low The most successful customers focus on generating inroads and insights Inroads: Get this to an overall level of engagement that sales can leverage Measures: Stakeholder engagement, multi-touch engagement, team-wide engagement Insights: Pay attention to how and with what they engage. Pass this along to inform sales plays
- We see people fall down on the hand off to sales You need to enable account level scoring It needs to be clear that the lead is attached to an account-level opportunity SDR/BDR teams can be a weak link You must be able to pass along insights ABM Module in Marketo ABM specific solutions like Engagio Or you need to be able to manage the follow-up cadence and lead disposition differently Lead object in Salesforce (zero dollar) Tools like Sales Loft
- Account level insights are key The fastest path to a return comes from combining data sources Combining predictive insights with intent can help with productivity Combining internal and external data can help with prioritization Not all intent data is created equal
- This scatter graph reflects the concentration of search results on the web for content related to a potential enterprise technology purchase. As we said before it’s critical, in our efforts, to minimize false positives and false negatives and in fact that is largely the point of purchase intent data It all comes down to rank and relevancy; you want to be tracking consumption of content that ranks highly in search results, because that reflects the majority of the purchase research behavior (or active demand) for your solution or the problem that it solves (thereby eliminating false negatives), you want to make sure that content is really relevant to what you sell in order to eliminate false positives from the equation What this graph shows is that there is a big difference between intent data drawn from highly-ranked content that is directly relevant being consumed on a site designed to support technology purchases as opposed to content that *might* be about what you sell being consumed in a broader business or consumer context not related to a purchase. A lot of the solutions out there are tracking these weaker signals in a broader context. They’ll tell you that their strength is scanning the broader web for more signals.
- Predictive and intent-based initiatives are by their nature account-based That means, gain, you need to be able to pass along or factor in account-level insights, scoring or prioritization in your marketing and sales follow-up Consider the tactics and solutions we discussed for ABM Accounts, leads or opportunities identified through predictive methodologies or through external intent signals require campaign-based follow-up (whether that follow up is by marketing or sales) They may not know or have engaged with your brand From the possible objectives identify/qualify/engage, the priority is ENGAGE To do this successfully requires context and content Your messaging needs to address what we know about why they are interested You should employ content that gets you the best response