Let’s brace ourselves for a hard truth. Trust in marketing measurement is already poor, and left unchecked, it’s poised to get 20% worse.
The pain that your organization feels surrounding B2B marketing measurement problems is real. Forrester’s Marketing Survey, 2024, revealed that 64% of B2B marketing leaders feel that their organization doesn’t trust measurement for decision-making. This hurts because marketing is a discipline with credibility that depends on data, facts, and insights, yet many marketing leaders don’t have faith in their company’s measurement when it matters the most.
Not having trusted measurement hinders marketing’s ability to get its job done. Optimization of marketing efforts requires data to inform adjustments. That can’t happen when the metrics used to describe performance aren’t trusted. And without measurement to clearly depict marketing’s contribution, securing the budget and resources necessary to drive business impact becomes a losing battle.
None of this is new, nor are the well-known contributors to the current state of marketing measurement (they include data quality, technology gaps, and the skills of measurement producers and consumers). All are aspects that B2B organizations continue to work to improve, but unfortunately, many B2B marketers will lose ground in these battles over the coming year.
Why Is Measurement About To Get Tougher?
We’re predicting that marketing measurement is about to get more difficult because of these compounding market forces:
- Buying complexity obscures so much. B2B sellers tell us that deal cycles have grown longer. Buyers tell us of the large quantities of individuals now involved in purchasing decisions. Persistent time-lag issues in detecting business impact grow more difficult with lengthened selling cycles. More people interacting with sales and marketing more times places more pressure on measurement systems already struggling to capture and make sense of their behaviors. Until vendor organizations recalibrate their business systems and processes, they will detect a limited portion of total buying interactions and will have to wait longer to understand results.
- Technology sprawl yields fractured data. The volume of technologies that make up the go-to-market technology stack results in disconnected data sources, and in turn, disconnected data is now a leading analytics challenge. Stitching together a cohesive picture of buyer behavior across these technologies is stretching the resources and skills of analytics teams — and this shows little signs of being alleviated.
- AI-inflated hope drives an expectation gap. AI has the potential to power meaningful improvements throughout B2B. This promise carries into widespread expectations that better measurement is possible by using AI to make sense of large volumes of data at speeds that humans will never replicate. But the distance between that vision and the current state of B2B marketing measurement should be counted in years, not months. B2B planning, processes and data aren’t yet in shape to meet AI’s potential. Stakeholders of all types will struggle for the foreseeable future to make sense of and develop faith in AI-driven views of performance. Expect a prolonged period of experimentation, missteps, and resets before B2B marketing analytics teams come anywhere close to cracking this code.
- Measurement can’t keep up with a renewed emphasis on reputation investment. B2B marketing investments have traditionally skewed toward capturing and advancing demand and so, too, has the focus of marketing measurement. But there’s growing recognition that demand efforts are not enough, and selling organizations must do more to influence buyers before they enter active buying cycles. Reputation spend now represents nearly one-quarter of marketing program investments, but we’re not seeing similar prioritization among what marketing leaders measure. Measurement analytics teams currently fall short in the skills and capabilities to measure this area that they’ve traditionally deprioritized.
What’s To Be Done?
Each of these market forces are larger than measurement, and there’s little that your analytics team can do to hold any of them at bay. What will separate the winning organizations from the rest is how they respond. In the face of these forces, here are a few actions that you can take to enhance your organization’s trust in marketing measurement:
- Tune your processes to buying complexity. Do the work to make it easier to link buyers to opportunity records, and work to capture not only self-guided interactions but personal ones, as well.
- Economize the B2B tech stack. Squeeze out duplicative capabilities found in best-in-breed solutions in favor of the broader solutions of platform providers. A more consolidated set of technologies will carry less overhead when it comes to data preparation and consolidation.
- Set clear reputation objectives. It’ll take time and resources to create comprehensive approaches to measuring reputation. In the meantime, start small by working with stakeholders to be sharp about setting reputation objectives and select a handful of available indicators that can show progress.
- Pair AI efforts with insight activation. Marketers are right to be excited by the potential of AI. At the same time, there’s a clear need to enable them to work more productively with the analytics already available. Marketing analytics teams need to redirect more of their time toward enabling their stakeholders to drive better results using existing resources. Doing so will better prepare them for the potential that AI is bound to unlock.
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