đ”đ»ââïž [ABM Case Study] How Backbase built an AI-native ABM motion
A detailed breakdown of how Backbase is building a global ABM function and integrating it in GTM AI system.
In this case study, weâll share:
How Tim Rutten reorganized an entire marketing function around strategic accounts and got sales aligned in six regions
How Backbase built their own AI-native go-to-market operating system in-house, what they automated, and what they kept human
The five-stage account velocity framework they use to measure ABM progress and pipeline contribution
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What led Backbase to try ABM
Weâve been working with @Tim Rutten, CMO at Backbase, for the past 9 months. Backbase is an Amsterdam-based fintech company selling AI-native banking operating system. Their customers are mid-to-large banks globally: retail, commercial, private banking, and wealth management institutions that need to modernize their complete operations. The sales cycle length is 18-24 months.
When Tim reached out in 2025, he had just taken the CMO seat. Backbase had a strong product, but narrow global market: 3,000 accounts worldwide.
The marketing function was organized the way most enterprise marketing functions are organized. Brand, content, digital, and field each had their own KPIs, their own interpretation of what ABM meant, and their own opinion on how marketing should work.
Tim wanted a cohesive full-funnel AI-native ABM motion that unites brand, demand, sales and client success into one system and make sure every region runs it. And do it while Backbase was repositioning themselves as an AI-native company in a banking industry that is very slow to innovate.
As always, we started with a small scope pilot program with the US wealth management team to build the motion and integrate it into the GTM AI system Tim was building earlier.
Backbase had a strong presence and credibility in Europe, but wasnât known in the US. The US wealth management team was relatively small and new. We decided to use it for a pilot program to see whether a structured ABM motion could help to fix the slips between marketing and sales, and engage strategic accounts unaware of Backbase.
The pilot generated 6 discovery calls with enterprise wealth management accounts. But what was most important is that it created an internal demand from other regional teams to replicate success.
As Tim said:
âMy CEO is making a full call now: how fast can all of my teams, all of my regions, all of our territories work this way, report this way, and basically play the game this way?â
5 keys to pilot success
1. Pick the right person to lead it
The ABM lead is a program driver. A person who pushes it forwards and unblocks the challenges. Here is how Tim describes this person: âYou know the type of talent that will pull through, will unblock it, will give you the right phone call at the right moment in time to make progress. Critical.â
2. Pick the right region
As I mentioned, we ran the first pilot in the US, a market where Backbase needed to build credibility from scratch. Tim chose the region where the right sales talent was in place, they were building a new sales motion, so could easily integrate ABM. He knew those people would become amplifiers if the pilot worked.
3. Build the right cross-functional team
Timâs selection criteria for who to bring in:
âGo through that flow and literally ask the right people, hey, who should we bring into the team? Because they know theyâre operating on the ground each and every day. I think in five minutes, you have the right people to work with. Theyâre all going to be fired up after a 15-minute call.â
He was looking specifically for people who were change-prone and aware that the old motion was not the best path forward.
4. Setting up the right expectations
Tim deliberately did not put a revenue target on the pilot. âI didnât inflate the numbers or the expectations by saying I need $10 million out of this or 10 opportunities. Who am I to tell you what itâll be? I have no idea. But my hypothesis was that this way of working was going to be meaningful. So not putting the pressure on the team, I believe, was helpful.â
The only target: follow the complete full-funnel methodology, report back every other week, and show the positive signals that the program works to continue investing in.
5. Integrate ABM into AI-native GTM
The full story is below.
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AI-native ABM function
Before ABM, Backbase built their own AI-native GTM operating system in-house. The first step was developing the signal engine.
They had a renewal coming up for their ABM platform. Tim concluded it was a black box: keyword-driven, hard to defend, producing signals not meaningful for a 12-18 month enterprise banking sales cycle.
âA keyword search is not an indication of a bank actually buying.â - Tim Rutten
He terminated the contract and used that funding to build a custom signal engine from scratch, combining:
Third-party signals
Social signals from LinkedIn
Sales signals from Salesforce via People.ai,
First-party signals from marketing campaigns and events.
âIt basically gave us the following: we now have all the data. It is white box. I can fully control what goes into this. And we can leverage it as we please, which is literally the fuel to even consider becoming an AI-native operating model over time.â
That signal engine became the foundation for their full GTM OS which we aligned with Full-Funnel ABM methodology. Here is how we integrated it.
Integrating ABM into AI-native GTM OS
One of the most common mistakes I see with using AI in ABM programs is automating the process before creating a detailed SOP and a quality benchmark. They take a poorly defined process (e.g. You are an account researcher for Backbase. Run a research of this company), hand it to an AI, and get bad outputs.
Yes, you run it faster, but it doesnât mean you have a better quality.
Here is the best anecdote that describes the problem from another Senior AE from Backbase, Piotr Wybieralski:
Gemini said to me: this buyer has this initiative and seven key use cases. Then I researched manually. What Gemini picked up was two years old. Two years in AI is like medieval. If I wrote an email to that buyer saying âthe seven things youâve mentioned,â Iâd look like an idiot.
Our approach with Backbase was the opposite. Before using AI, we worked through the core ABM process manually with the sales reps and ABM leads, that we could potentially automate later. Once we have created detailed SOPs and workflows with the examples, we started rebuilding them with AI:
running reviews with the team after each iteration
refining the prompts
the scoring and prioritization principles
the output format
All until the quality of AI output matched the results of manually ran processes. Here is the breakdown of the processes that are now fully AI-driven vs human-led.
Fully AI-driven ABM processes:
1. Account prioritization
The agent reviews and prioritizes 3,000 strategic accounts continuously using the signal engine Iâve described earlier and our account prioritization framework. Every week it highlights account engagement which allows all ABM teams to define the next best CTAs.
2. Account research
When an account is moved to Future Pipeline list, AI runs deep research including strategic initiatives, recent leadership changes, regulatory context, and buying committee activity. The output is reviewed by the ABM manager before sharing it with a sales rap.
âAI does research at a level that is completely superhuman. The level of detail and context it can digest, external as well as within your CRM, is second to none.â - Tim Rutten
3. Buying committee mapping and enrichment
An agent queries external databases, finds the relevant contacts across target accounts, and transfers data records directly into Salesforce. The manual version of this process was one of the clearest cases of wasted human capacity: repetitive, time-consuming, and not requiring any judgment.
âNo person should spend their time there. Itâs just silly.â- Tim Rutten
4. ABM Content customization (80% of the work)
Account love letters, ICP cluster webinar decks, newsletter research and drafts are now prepared by AI agents. AI generates the raw material, a human reviews, refines, and publishes.
Human-led ABM processes:
1. Deciding which accounts should get 1:1 attention
Deciding which account gets one-to-one focus, is a manual decision made by the ABM teams. They review what is actually happening in the account right now, what relationships they have, the insider information that no AI can capture, etc.
2. Outreach and relationship building
Commenting on a stakeholderâs LinkedIn post, sending a DM, showing up at an event, getting a meeting through a CXO podcast - these activities help to connect and establish strong relationships with the strategic buyers.
3. The executive relationship layer
Backbase runs a podcast program where Tim personally hosts conversations with target account executives. They run a community for women in banking across target accounts.
âIâm building communities in a very respectful and thoughtful way to just connect people with people. These programs generate access to senior buyers that no amount of automated outreach can replicate. They require a human who can host, listen, and follow up with genuine interest.â
What Backbase tracks and why
The measurement model Backbase uses is built around account velocity: how accounts move through the motion stage by stage, and what marketing contributes at each stage.
Here is the full framework.
Stage 1: Cluster ICP accounts
Cold accounts that fit ICP criteria and have demonstrated light engagement or been prioritized by sales.
Goal: awareness and nurture until an account hits the engagement threshold.
Marketingâs job: thought leadership content, newsletters, collaborations with industry communities and podcasts, events.
Stage 2: Future pipeline accounts
Accounts that have crossed the engagement threshold.
Goal: research and validate account needs, understand where they sit in the buying journey.
Marketingâs job: account qualification, account research, buying committee mapping, enriching contact data, building playbooks to engage the full buying committee.
Lagging indicators: account engagement, account penetration (connections made with buying committee members), accounts with insights collected via direct engagement.
Stage 3: Active focus accounts
Accounts with a high likelihood of converting into a sales opportunity.
Goal: generate a discovery call.
Marketingâs job: personalized content hubs, co-creating one-to-one plans with the AE, in-depth account and contact-level engagement analytics, personalized solutions.
Lagging indicator: discovery calls and strategy sessions booked.
Stage 4: Sales opportunities and pipeline value
Accounts in the pipeline.
Goal: accelerate the sales cycle and win the deal.
Marketingâs job: shifts to supporting the deal directly: co-creating business cases, preparing buying committee content for specific stakeholders, collecting relevant customer stories, preparing product overviews.
Lagging indicators: pipeline value co-created with sales, sales opportunities generated.
Stage 5: Revenue
Two core metrics: total revenue broken down by new revenue, expansion, and renewals; and sales pipeline velocity.
The logic behind this system is that marketing has a defined role at every stage. There are leading indicators it controls and lagging indicators it shares with sales. There is no separate marketing dashboard.
When we created it for the first time, Tim said:
âI can literally see accounts moving through over time, and I can show the actual impact on which moment in time, which campaign, which touch point mattered and why, and how it then relates into the pipeline.â
Before the US wealth pilot launched, around 60-70% of Backbaseâs global target account universe was cold. After 9 months of running the full motion, that number has flipped: 60-70% are now aware, showing the first signal, or actively engaged.
What makes ABM implementation successful
We asked Tim what he would tell a fellow B2B CMO setting up an AI-native ABM motion. Here are 4 pillars he has mentioned.
1. Get alignment with your leadership before launching the program
CMO and CRO/VP of Sales must be on the same page on:
How the motion should
What the KPIs are
Why is this way of working better than the old one?
âIt has to start top down. And that is not enough. You need an operational layer that drives discipline, cadence, clarity, and accountability.â - Tim Rutten
2. Be hands-on to drive change
âA spreadsheet or slide deck exercise you give to a few people in your team, and youâll go focus on your day-to-day. Thatâs not the leadership I would bring to drive change here. Be very close to the shop that youâre running. If you are not in the details and you donât understand how the operation really, really works, youâre not going to get there.â - Tim Rutten
3. Be the champion all the time
There will be pushback, delays, and all the standard change management challenges. âYou need to be the strongest player to continuously fly the flag and keep pushing.â One to two quarters to show real results. Six to twelve months to bring the full org to the new model.
4. Build your own GTM infrastructure
âIf you just apply volume and time to where the market is now moving, how do you differentiate? Everyone will have access to Claude, to Cowork, and their content will be relatively similar to yours. To really transform appropriately, own all the data, own the majority of the infrastructure, and really transform workloads across all angles: sales, marketing, the full go-to-market motion.â
Tim calls this go-to-market alpha.
âYour go-to-market and the way you go to market is IP. Because everything is gonna be commoditized. Content is commoditized. Strategies will be commoditized. So you better have a very unique view on how you drive your full go-to-market motion.â
Watch Full-Funnel Live - How to build a global, AI-native ABM function.
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On March 26, we hosted the 7th Full-Funnel Summit. One of the most popular sessions was hosted by Tim Rutten, CMO at Backbase, where he shared how he created an AI-native GTM system. After the summit, a lot of people reached out to both Tim, asking where they could learn more, and me.
Weâve been working with Tim and the Backbase team for almost a year. So instead of repeating the summit keynote, we decided to chat about how to build a global, AI-native ABM function.
đĄ Tune in to learn: â
â The step-by-step process to build a global ABM function gradually
How to structure cross-functional teams and handle the resistance
How to track ABM performance across long sales cycles
How to integrate AI in ABM: an overview of the core processes and signal engine