Comparing Stand-Alone and Embedded Intent Data

Jul 11, 2019 | Author Ed Marsh

ABM Software's Intent Data Infatuation

Like high schoolers pairing up for the prom, account-based marketing (ABM) software vendors have been glomming onto third-party intent data solutions a lot lately.

Announcements and offerings include:

The application of third party intent data to ABM makes sense (although account-level signals only provide hints rather than powerful contact targeting insights).

But is a package deal the best solution?

That's the interesting question raised by Aberdeen's report "Demystifying Purchase Intent Data" which suggests:

"SKIP THE EXPENSIVE SOFTWARE Many ABM software providers are trying to bundle intent data into a large software and integration commitment. Unfortunately, this is expensive, involves a great deal of effort focused on redoing a martech stack, and takes the focus away from getting value from intent data by driving sales. Companies have enough software. They just need to make their existing software smarter with intent data."

It's important to note two facts. First, Aberdeen is no longer an independent research firm, although many still assume it is. It's a bit of sleight of hand that its "reports" are not sales collateral for the data they sell. Second, that data has evolved. Aberdeen partnered with Bombora in 2016 because of Bombora's "reach" before buying Big Willow in 2018 to acquire the largest pool of data.

Let's put those issues aside and parse Aberdeen's argument.

"Skip the Expensive Software"

"ABM software....trying to bundle...large software and integration commitment....expensive...Companies have enough software."

Is account-based marketing a buzzword? For sure. But "target account sales" are fundamental, and I'd argue that ABM is merely a digitally enhanced version of what great revenue growth teams have done for decades. The short-term value of the ABM discussion has been to revive the topic that had been neglected.

Companies need to have a target account strategy which encompasses all aspects ranging from thoughtful target account identification through success, and incorporates best practices like account-specific/role-specific/even contact-specific content creation. (If you're embarking on an ABM campaign, start with some study and realistic resource planning. Rob Leavitt (@RobLeavitt) of ITSMA is a software-agnostic resource.)  

The software is a different question. Whether a company should invest in ABM software (i.e. Engagio, Triblio, Terminus) is a largely unrelated question. For years great companies ran ABM programs with paper files. There's certainly a shiny gadget appeal, and ABM software offers appealing capabilities for target account marketing at scale. Aberdeen is correct that there's cost associated beyond the subscription itself. The integration and learning curve — even ongoing execution — require resources. That's a consideration factor, though; Not a reason not to use software.

My take on this argument is that companies need to decide whether they need software based on organizational, resource and strategic factors — not the question of intent data bundling.

The "Achilles' Heel" of ABM is "Accounts"

What's true is that ABM software isn't a silver bullet. In fact the term "Account-Based Marketing" may actually contribute to execution frustrations. Why?

Accounts don't buy. People make buying decisions.

That's the inherent conflict in the promise of automated ABM at scale, and why great practitioners of ABM are so focused on identifying key players and developing one-to-one relationships built on insights and credibility, rather than a "touch" metric. (Want to learn more about targeting CXOs? Sharon Gillenwater (@CXO_Insights) is a thoughtful resource.)

It's also the reason why ABM desperately needs intent data, and why account-level intent data only provides a fraction of what's really needed.

Most intent data only reports anonymous activity at the account level. Some providers then "overlay" contact details for randomly selected individuals that happen to meet the IDP, but who aren't connected to the observed activity. That's not without value. If you are trying to do ABM at scale with 1,000 accounts, it's helpful to know which 50 should get more immediate attention. The typical solution at that point is to blast everyone in those active accounts, by role/function/title, with paid ads.

But accounts don't buy. People buy.

And they buy for reasons which we can only start to understand with some nuanced context of their activities.

What ABM really needs is real-time insight into the actual people and specific intent actions that are being taken by players in target accounts.

"Make their existing software smarter with intent data."

So where does that leave us?

I contend that software doesn't sell anything.

I've seen phenomenally successful sales people with archaic technology (albeit less efficient than they might be) and ineffectual ones with tech stacks that would make anyone envious.

Just as people buy, likewise, people sell.

So for intent data to succeed, it has to help sales people. Integrations with CRM & marketing automation systems, real-time alerts, and thoughtful workflows that suggest appropriate enablement content can mechanize certain functions. That's the role of software. Perhaps as AI advances, smarter software will be able to sell. But for the foreseeable future, reasonable best practices focus on making salesPEOPLE more effective.

That requires knowing the person who is active (often people) and the context of the action they've taken. Without that, you're simply throwing the proverbial stuff on the wall to see what sticks.

My take on this argument is that it's people, not software, that needs more info. Further, the info that they really need is rarely provided.

Comparing the Cost of Embedded Data

Is intent data that is embedded in ABM (or other) software more or less cost effective than stand-alone data? We can answer that question different ways.

Embedded purchase intent data "pros" include:

  • likely cheaper on a monthly basis
  • may require a longer subscription commitment
  • likely require less time and attention for configuration and integration
  • limited activation opportunity

So if you want to simply check another martech box, this may be good enough. Based solely on the subscription cost, it will likely be the cheapest access to intent data.

However, embedded buyer intent data "cons" include:

  •  you have no choice about which behavioral intent data to use
  • account-level only (missing the critical contact-level information necessary to really leverage the insights)
  • missing granular detail (based on topics versus a custom-built algorithm) and no detail on nature of signal or stage in buying journey
  • likely miss the opportunity to use it for other use cases across customer lifecycle
  • no file with data in aggregate to conduct analysis

Those cons have some substantial net cost implications.

  1. If the data can't be used across multiple marketing, sales and success functions, then there's either opportunity cost or redundant subscription cost to use it beyond ABM.
  2. If the goal of your ABM program is to drive revenue, then not knowing who the person is that's active is a major flaw that makes it practically impossible to make the transition from account-level interest to sales results.

Standalone data "cons" include:

  • likely more expensive
  • more research required to select an option
  • more work required to get started

Standalone data "pros" include:

  • integrate it with all software via marketing automation/CRM connection
  • use the same data for multiple marketing, sales and success use cases (including other ABM and demand gen-related marketing applications of remarketing and event marketing) 
  • option to select the data model, collection method and attributes that are important to you
  • contact-level intent data option available

Function, Cost and Return on Investment of Intent Data

Here's the bottom line.

Companies should:

  • decide whether/which ABM software is right for their business
  • consider all applicable uses cases and plan overall purchase intent data orchestration
  • plan their behavioral intent data activation
  • decide whether/which purchase intent data is right for their business (based on contact-level versus account-level signal, breadth of reach, privacy considerations, and granular, contextual detail)
  • finally, explore whether add-on embedded data satisfies the business requirements and compare the prices for options which do so

There are numerous collection methods and intent models. Selecting the most convenient may not be the best option for your business. Our free guide to buying and activating intent data may be a great place for you to start your comparison of options.


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