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  • Jason Lucey

From Assumptions to Evidence: The Power of Marketing Analytics Intensive "Test - Learn - Grow" Programs


It’s a new year. Everyone is excited to craft their strategies, plan their campaigns, develop messages, target audiences and get to market.  Everything flows downstream, stage by stage, like a waterfall. But what if the core of your plan--its strategic assumptions--are nothing more than shaky guesswork?

 

Many marketing programs begin with an ideation session and a creative vision. Strategists take those ideas then research, plan, and craft a campaign that then becomes a media plan, a channel strategy, and all the supporting pieces. Everything flows downstream from the initial vision. A/B testing may exist, but it's often limited because the main strategy is already set.

 

The drawback? Basic strategic assumptions, sometimes mere opinions, rarely get re-evaluated or validated, especially after budgets are allocated. I've seen many beautifully executed campaigns built on shaky assumptions ultimately fall short. These are the risks of the "Strategy Waterfall" approach. 

 

"Test - Learn - Grow" for Evidence-Based Strategy

This is where "Test - Learn - Grow" enters the scene.  It's a paradigm shift, transforming marketing from a static waterfall into a dynamic ecosystem. We embrace agility, testing assumptions early and often in fast-moving channels like paid search and social media.

 

It starts with a test and learn program, often an A/B test, but with a crucial twist -- learnings are prioritized as highly as business impact. We intentionally loop the learnings back into the over-arching strategy, constantly validating assumptions and evolving based on data, not hunches. This iterative approach unlocks three distinct advantages over the waterfall method.

 

  • First, agility wins. We get to market faster by testing small and adapting quickly.

  • Second, we broaden our analysis and to gain insights that go beyond tactical optimizations.

  • Third, we recognize assumption for what they are and build an evidence-based understanding of what is strategically important for you, your prospects, and your customers.

 

The "Test" Phase: Diving into the Marketing Data

The test aspect of this program really begins as simple A/B testing. It's not about impressive complexity, but speed and learning. Throw a couple different ideas out there and very quickly understand what is resonating and what's not resonating. This rapid experimentation is ideal for agile channels like paid search, social media, or even qualified email lists.

 

This approach prioritizes speed and efficiency. We cast a wide net with diverse angles, maximizing learning opportunities while still driving results. Unlike the waterfall method's heavy upfront planning, we minimize setup friction and embrace the iterative process. We're not afraid to adjust course based on what the data tells us, ditching assumptions that don't hold water and doubling down on what works.

 

The "Learn" Phase: Analysis with a Broader Mindset

The "Test" phase gathers data, but the "Learn" phase is where the data becomes meaningful.

 

Too often in A/B testing programs, the findings are used for simple tactical optimization. Ultimately this is a reductive process. Poorly performing ads are turned off and budget pushed into the best performing ads. Over time, the experience gets "dialed in" but performance will plateau.  This does not support long-term growth. It also limits the potential of these programs as they become increasingly specialized and disconnected from the full marketing vision. 

 

Going beyond surface-level metrics, we delve deeper into the data, asking questions like:

  • What do keyword tests reveal about customer mindsets and intent?

  • What do users value on our landing pages?

  • What do their behaviors indicate about their motivations?

  • What unmet needs or pain points can we address more effectively?

 

By answering these questions, we gain a rich understanding of our target audience at the individual level. This knowledge isn't just for tactical optimizations; it's the foundation for strategic evolution.

 

Grow: Building an Evidence Based Approach with Contextualization

This knowledge is not just for tactical tweaks; it's the fuel that propels strategic growth. We embrace an evidence-based approach. This means building campaigns and media programs on the bedrock of customer reality, not stakeholder opinions. This is where contextualization truly shines. By weaving together insights from the data collected and feeding them back into the underlying strategy, we can surface opportunities to meet your audience's needs and what understand what your marketing needs to become.

 

This knowledge opens the door for:

  • New channels: Explore previously unconsidered avenues to reach your audience.

  • Better messaging: Refine messaging based on actual response and behavior data.

  • Website optimizations: Tailor the customer journey for increased engagement.

  • Retention programs: Build loyalty and nurture long-lasting relationships in response to

  • Sales collateral: Empower your sales team with tools based on empirical insights.

  • Awareness efforts: Spark interest in ways that may not have been considered before.

 

"Grow" is the culmination of the "Test - Learn - Grow" cycle. It's where we harness the power of data to transform marketing into a dynamic, ever-evolving engine of sustainable success and increasing customer relevancy.

In Summary

This data-driven methodology starts with rapid A/B testing in agile channels, casting a wide net to gather insights and challenge assumptions. But it's the additional analysis and strategic interpretation in the "Learn" phase that unlocks the potential.  This knowledge isn't just for tactical tweaks; it's the fuel for strategic evolution. In the "Grow" phase we reimagine the customer journey, explore new channels, refine messaging, and build campaigns grounded in the reality of your audience, not assumptions.

 

"Test - Learn - Grow" isn't just a methodology; for some organizations it can be a key step in the shift toward embracing agility, continuous learning, and reliable evidence-based growth.

 

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