Future Proof your Marketing with Commercial Acumen and Intelligent Testing

It’s tempting to swirl or get paralyzed by volatility if you’re a marketing professional today. 

For starters, 3rd party cookie deprecation on Chrome is imminent. That’s one more nail in the deterministic audience coffin, combined with more privacy legislation across the world. We’re being bombarded by AI tools that promise to either transform our businesses or take away our jobs. If you’re a growth or performance marketer, you’re also lamenting the glorious CAC efficiencies that you enjoyed during the pandemic. 

While I love a doomsday vent as much as anyone else, I think we have a valuable opportunity to hit reset. 

How? We find a workable middle ground - somewhere between a ‘head in the sand’ luddite mindset and the irrational exuberance of techno-optimists. 

We double down on evergreen fundamentals as well as build a testing sandbox to prepare for the future. 

Here are a few provocative questions and considerations to get started: 

Evergreen Fundamentals : Solve for the big picture

1. Commercial acumen: Uplevel & revisit strategic decisions 

• Which product  /  audience  / distribution channel drives top line & margins? Are your marketing investments lined up appropriately to capture value? Are there trade offs or hard decisions on product pruning or cannibalization you’ve been putting off?
• Are you spending to re-acquire the same customers every 2-3 months via paid marketing instead of building loyalty via your owned channels? If so, you likely have a product engagement problem, not a marketing one.  
• Are you investing appropriately in demand creation vs. demand capture? If you’ve over indexed or exhausted your ‘low hanging fruit’ audience in the last year, you should now invest in building consideration with undecided users. This may not yield short term returns, but will likely pay off longer term. 
• Is your marketing measurement approach giving you a true view of impact across your paid, owned or earned as well as online and offline channels? It’s important to remember that click-based attribution is increasingly unreliable in a world of more user opt-outs, cross device / browser tracking restrictions and growth in unattributed traffic from messaging platforms (eg. Whatsapp) and LLM chat interfaces. 
• Are there pricing changes you can test this year?  Increases for user segments that are relatively inelastic? Adjustments to drive unit volume for elastic segments? 

2. Your value proposition and big creative idea

This is your enduring source of differentiation in a sea of commodification. While AI tools could help in the idea generation phase, remember that LLMs are inherently skewed by the safety of status quo i.e. available training data and are likely less poised to deliver breakthrough, yet on-brand, ideas.

3. Cross-functional collaboration for sustainable growth

• Reduce silos across teams by instituting more “shared” higher level OKRs  vs. fragmented ones that map to narrower goals. 
• Investigate leaky buckets & shaky handoffs Eg. Is the “acquisition” team just throwing users across the fence without ramping them up? 

4. Invest in relationship “depth” for high stake situations

When automation is everywhere, relationships become more, not less valuable. This could be your marketing team collaborating with finance on ROI goals or your sales team pitching to a CIO. At the end of the day, the ability to strategically influence and manage people has never been more important. 

Testing Sandbox:  Develop hypotheses.  Learn, iterate and scale intelligently

1. Invest in First Party Data

• If you don’t have a sizable first party data set yet, build it in a privacy forward manner and reduce reliance on third party signals or identifiers. 
• Your first party data set is your real-time steer. Use it to inform media platforms on what audiences and signals are valuable to you. 
• When you have enough scale:
  • Test and compare the effectiveness of targeting lookalikes of your most engaged or loyal cohorts vs. other native targeting capabilities (eg. in market audiences on Google) across platforms. 
  • Enrich and augment your 1PD by partnering with brands that talk to a similar audience via a privacy preserving data clean room. 
  • Consolidate your first party audiences with contextual signals & activate with high-quality data-rich publishers. 

2. Figure out your relationship with AI

• Start small if you don’t have resources available. Prioritize use cases that matter to you. 
• Improved efficiency & productivity are low hanging fruits for AI in marketing, so that’s often a good place to start.
  • Could AI enable you to adapt your big creative idea downstream? Scale long tail asset production across languages or seasonal promotions across fragmented markets in a cost efficient manner? 
  • Other popular use cases for Gen AI in marketing are editing or repackaging content from one format to another eg. transforming static images to Instagram reels or creating sharable short clips from long form videos and podcasts. 

• If you have resources available,  test combining your proprietary data and specialized expertise with the scale of LLMs [trained on public data sets] to create new revenue streams or a superior customer experience.  This can enable you to build competitive advantage in a level-playing field, but could entail a rebuild of your core offering. 
• Above all - make sure AI significantly enhances the customer value proposition before you make irreversible commitments. Always validate with customer feedback, don’t get swayed by FOMO.