Difficult times are ahead for marketers.
The global economy is heading for a recession. This will most likely lead to a lower purchasing power of potential customers. Marketers will have to justify their budget decisions more than before and be able to demonstrate success.
At the same time, we see that performance marketing has changed. Third-party data, which used to drive almost everything that guaranteed success in digital marketing, has become unreliable.
Even, Meta themselves, have confirmed, that, due to iOS14, targeting and measurement have become noticeably less accurate.
1) Strong brand- and community-building
Not so long ago, it was possible to build a business model based on arbitrage. You could launch an online shop, sell a generic product, buy relevant traffic and optimize it so that the traffic acquisition costs were cheaper than the lifetime value of the customers acquired. From this point, you could scale up and build a solid business with no real brand attached to it.
The absolute foundation for this was precise (almost spooky) targeting and stable conversion attribution. Now, with the rollout of iOS14, that’s no longer the case. This presents challenges. At the same time, the rise of Shopify also saw a steady increase in the number of shops for all sorts of products. Today, there are hundreds of shops for all kinds of products.
So, more than ever, e-commerce businesses shops need to know how to differentiate themselves. The best (and often only) way to do that is by building a strong brand. Ideally, a brand that is driven by people who are at the forefront. That has always been the case. But with the demise of pinpoint performance marketing, creative brand building must once again take a much greater place in the media mix. Only when this basis is there can you build on it and scale up with advertising.
2) Server-side tracking
At the same time, Google Analytics just announced they will ultimately sunset Universal Analytics and stop its development. All of its future endeavours will be invested in GA4. Therefore investing in setting up GTM Server-side & GA4 as your new measurement stack will be worth the effort.
3) In-house data expertise
In a recent blog post, Adverity identified the three cornerstones for high-performing marketing teams to become truly data-driven:
The right people are just as important as the right technology, and both together can only make a company truly data-driven with the right culture.
Companies today have vast amounts of data, and making sense of it and turning it into insights and deriving action from it is a full-time job. It requires specialist skills and is so critical to the success of your business that it should not be outsourced. Especially in these uncertain times, a strong data or BI department can make all the difference.
4) Focus on CRM and retention
With the death of the third-party cookie, advertising will become less accurate. This naturally means that the cost of acquiring new customers is rising. If you still want to stay profitable, you will have to acquire revenue elsewhere than from new customers.
For this, re-activating past buyers is a good strategy. During these uncertain times, increasing your customers lifetime value and retention rate will be the cheapest method of generating additional revenue.
5) Market mix modelling
Measuring ROI for your different marketing channels accurately is the basis for rational budgeting decisions. If you therefore cannot attribute revenue to marketing touchpoints your media buying will inevitably become less efficient. A recent BCG survey also confirms this, finding that marketers expect a 22% reduction in marketing ROI due to the pending third-party party cookie depreciation.
While marketers are on the hunt for new technology, still capable of providing such insights, there’s a hidden champion technology on the rise (again). Market Mix Modeling currently gets a lof of attention in the industry.
In a recent blog post “The future is modelled” by Meta, the writer describes MMM like this:
“Marketing mix modeling (MMM) is a tool that has been around for more than 50 years. Some form of it is likely already in use in most organizations in the RMG industry. If attribution is building a picture of performance from the bottom up (user-level), MMM is using statistical modelling to give a top-down (aggregate) view of how advertising is performing for both active customers and acquisition.”
And also other tech giants have jumped on the topic. TikTok announced an MMM partner program in a recent blog post. Google just published their own MMM package for data scientists.
Despite being an old technology, many players in the industry see a good timing for calling out a renaissance for it.
You might ask why?
The biggest challenge with MMM has always been painting a complete data picture. The model evaluating the marketing mix is always only as good as the underlying dataset. Creating this gapless set of all marketing activities, that happened during a specific time frame, was often not only a technical but also an organisational challenge for many companies. However, today the tooling for creating this single source of truth with all your marketing data has never been better. By using a strong ETL tool in combination with in-house data expertise you will be able to paint the complete data picture. And a good modelling technology on top of this data set has the potential to output better insights than attribution modelling was ever capable of.
Many environmental changes mean that also you, as a performance-driven marketing department, will have to adapt
Certain skills that were important before might have become less important and other new skills have entered the scene