Most companies don’t have a shortage of account data.
They have a shortage of usable account intelligence.
Information lives in the CRM, sales notes, call transcripts, marketing automation platforms, websites, annual reports, press releases, intent tools, and increasingly, AI platforms.
The challenge is bringing those signals together in a way that helps Marketing and Sales answer a much more important question:
What should we do next with this account?
I recently spoke with Chris Galloway, Head of Product and Marketing at Motivforce, about how his team is rebuilding its Creatio CRM to support a more sophisticated target account strategy.
His approach reinforces something we see frequently at Winalytics: before you can execute account-based marketing effectively, you need a CRM designed to help teams prioritize, understand, and act on account intelligence.
Why does CRM structure matter for target account strategy?
Traditional CRM implementations often focus on capturing activity: contacts, opportunities, emails, meetings, and notes.
A target account strategy asks the CRM to do something more.
It needs to help Marketing and Sales determine which accounts deserve attention and why.
As Galloway puts it, “The goal isn’t just to have more data in the CRM. It’s to make it easy for someone to look at an account, understand what’s happening, and know where we should focus next.”
That requires thinking about CRM design through the lens of decision-making, not simply data collection.
Why “cutting” might matter more than adding
Most CRM upgrades get framed as an exercise in addition: more fields, more integrations, more sources feeding in.
Galloway’s team started somewhere less obvious.
Before building anything new into the Creatio rebuild, his team analyzed fill rates across the existing CRM, field by field, and used that analysis to strip out the ones nobody was actually using, or that weren’t informing a decision either way.
“Most people assume a CRM upgrade means adding fields,” Galloway says. “We started by removing dozens of them. If a field wasn’t getting filled in, or filling it in wasn’t changing what anyone did next, it was just noise.”
That’s the clearest evidence of the decision-making-over-data-collection principle running through the whole rebuild. The fields that survived weren’t the ones easiest to populate. They were the ones that actually changed what Marketing or Sales did next.
What data do you need to prioritize target accounts?
A strong target account model starts by combining fit and engagement.
Fit tells you whether an organization looks like a customer you want to pursue. Depending on your business, that might include company size, industry, geography, revenue, existing solutions, or other ICP criteria.
Engagement tells you whether that account is showing evidence of interest: website activity, content engagement, campaign responses, meetings, Sales conversations, or opportunity history.
But increasingly, there’s a third layer: account intelligence.
AI makes it possible to augment CRM data with information from sources such as company websites, annual reports, press releases, earnings calls, conference presentations, and other public information.
The result is a richer picture of not just who fits, but why now might be the right time to engage them.
How can AI make CRM data more actionable?
AI dramatically expands the amount of account research Marketing and Sales can process, but only if there is somewhere useful to put that intelligence.
That’s an important part of Motivforce’s CRM rebuild.
Rather than asking a salesperson to manually research every target account, AI can help surface relevant information and augment what the organization already knows.
But the objective isn’t to fill the CRM with AI-generated summaries.
It’s to surface evidence.
In practice, that means AI-sourced intelligence doesn’t get written directly into an account field or layered on top of a rep’s notes. It lands as its own record, an Evidence entry: discrete, sourced, and dated, sitting alongside what Sales has already captured rather than overwriting it. That’s what preserves provenance, every insight stays traceable to where it came from and when.
“AI gives us the ability to bring much more context into the account,” Galloway explains. “The important part is structuring that information so someone can quickly distinguish what’s relevant from what’s simply more data, and so it never gets confused with something a rep verified firsthand.”
Has the company announced a new strategic initiative? Entered a new market? Changed leadership? Discussed channel growth? Is there something in previous Sales notes that connects directly to a current business priority? That’s the kind of thing an Evidence record is built to hold onto, along with its source and date.
Why does Sales activity still matter?
External intelligence only tells part of the story.
Some of the most valuable target account data comes directly from Sales.
Who did we speak with? What did we learn? What priorities did they mention? Who else is involved? What did they agree to do next?
That makes ease of use critical.
If logging a call or adding a note is cumbersome, the CRM quickly develops blind spots. And those gaps don’t just affect Sales, they limit Marketing’s ability to personalize campaigns, score accounts accurately, and determine the right next action.
A CRM supporting a target account strategy therefore needs to make capturing human intelligence as easy as possible.
Can your CRM tell you the next best action?
This may be the most important test.
Imagine opening your highest-priority account. Can you quickly understand:
● Why is this account a priority?
● What engagement have we seen?
● What has Sales learned?
● What relevant external signals have we identified?
● Who are we connected with, and who are we missing?
● What should Marketing or Sales do next?
If answering those questions requires opening five platforms and reading six months of notes, you don’t yet have actionable account intelligence.
The goal should be a CRM where someone can scan an account and move from data → evidence → action.
For Motivforce, that test has a literal home. Galloway designed a dedicated account Status page built around a pursuit narrative, the buying committee mapped by role, and a clear view of next steps. It’s built to be the place where the review happens, not just where the data sits.
Galloway’s team runs live pipeline reviews directly off that page, including the account reviews we conduct together as part of the Winalytics engagement.
Your CRM shouldn’t just record your target account strategy. It should power it.
A successful target account strategy isn’t simply a list of companies Sales and Marketing agree to pursue.
It requires a system that continually helps the organization decide where to focus, why an account matters, and what to do next.
That means building the infrastructure underneath your ABM strategy: strong lead and account scoring, clean CRM architecture, easy Sales activity capture, AI-powered account augmentation, and a clear view of the evidence supporting the next best action.
As Motivforce’s CRM work demonstrates, the objective isn’t to collect more information.
It’s to make the information you have, and the intelligence AI can add, easier for Marketing and Sales to turn into action.
