When it comes to predicting the buyer journey, how reliable is intent data for Marketers?
Predictive data is well-intentioned, but does it actually provide relevant intent data signals for your marketing efforts?
Marketing and sales have access to innovative, cutting-edge, solutions like never before. Technological shifts combined with required reactions to global pandemics, and emerging economic uncertainties have meant we are required to permanently be on our toes and to have the best solutions at our disposal that ensures sustained growth.
What becomes a challenge, is the maze of solutions that claim to have the silver bullet or the secret key to unlocking all your demand and lead gen needs and challenges. As new technology emerges, only time and learning curves teach us to distinguish between genuine, reliable solutions and those that are ambitious marketing rhetoric.
Intent or Predictive data solutions are probably the most contested in recent years. Clients of all sizes and budgets have had varying degrees of success (and even failures) with using intent data to guide strategy and campaign outcomes.
Whoever you ask, they have an opinion on intent data. Whether it is earned devotion through its successes or scepticism and absolute rejection of the idea based on internal or peer experiences.
Intent can be grey. Each offering has different variables and sources that define what predictive data actually is, providing an uncharted outcome for your marketing outreach. There is no universal benchmark or framework but only what internal developers and product teams have defined as predictive data. Furthermore, it’s harder for marketers to establish what variables are also segmented (reliably) to ensure that the predictive data they are purchasing or using for a campaign does indeed, have an actual, relevant signal that is pertinent to their product/solution offering.
Predictive intent is not a negative though. In fact, it’s immensely valuable to any marketing and sales function. The difference between good and bad intent data is:
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How data is initially gathered
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How account variables are scored (content consumption, relevance, tactic engagements, etc)
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The segmentation that takes place
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What are the benchmarks? (e.x. frequency, historical engagement types)
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Differentiating specific intent signals across each account
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Is it benchmarked against real-time engagements?
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Is the data specific and relevant to your particular product/solution and target market?
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Are you able to review all engagements to help you make an informed decision on sales escalation or further nurturing?
Most of us have heard or practised the mantra about “bad data in equals….” you guessed it!
Whilst intent data is not a bad or negative input that leads to bad output, intent data is simply a data layer to help structure your campaigns. It is only when campaigns are in full flight that you begin to see the true, real-time intent signals and engagements that can define and validate the true intent of an account. Successful marketing puts the customer first, their experience and journey, personalising as much as possible.
What intent does is give you, is an initial idea of where that account has been at a point in time. As marketers it is then on us to engage that account further, using those real-time campaign tactics to further benchmark and qualify the intent before we progress to sales teams. As intent data evolves so too will the understanding across marketing and sales functions. Understanding some of the key successes and pitfalls now, will not only save you time and budget but ensures that there is an enhanced alignment between marketing, sales and ultimately, the prospective customer.
B2B Media Group partners with the world’s largest B2B technology brands and agencies, working with reliable data, technology and marketing solutions that increase their marketing and sales performance.
