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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.
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