General Manager
Data driven marketing has quickly become a necessity, with challenges such as cross channel attribution, the introduction of privacy regulations (like iOS 14.5 and GDPR), and even more commercial scrutiny on the bottom line. With all of this in mind, what key strategies should brands explore to achieve growth through data-driven marketing?
Pivot Your Focus from 3rd Party Data
Whilst Google has recently put a hold on plans to depreciate 3rd party cookies, advertisers should still be focusing on consented data capture - whether that be through website infrastructure, to brand initiatives that add value to the customer such as incentivising account set-up, loyalty programmes or cross brand.
At Vervaunt, we have developed our own proprietary tool, Census, which has been helping clients gather these valuable data points to maximise their return on investment. Census is a post purchase check-out app which gathers zero party data which we can then leverage through performance marketing.
The Census app is rad. Super simple concept but very powerful for providing the foundations for experimentation. The childwear brand example is a testament to this.
Example:
A luxury childwear brand found through post-purchase survey data that gifting was a key reason for purchase, even outside of the traditional gifting periods. This then resulted in the roll out and testing of BAU focused gifting activity, ensuring that we’re optimising marketing activity to align with interests throughout the year.
Value-Centric Measurement
Post iOS 14.5, the landscape of measurement has evolved. Overnight, we lost accuracy in targeting algorithms, saw the introduction of modelled sales data and a significantly shorter attribution window, resulting in rising acquisition costs and a decreasing ROAS. In light of all of these challenges, brands have become focused on incrementality driven through their marketing mix, and learning through experimentation, with randomised controlled experiments the gold standard.
Developing a clear understanding around metrics such as Customer Acquisition Cost (CAC), Marketing Efficiency Ratio (MER) and Customer Lifetime Value (CLTV), instead of fixating solely on platform-specific Return on Ad Spend (ROAS) is allowing brands to evaluate overall site performance in conjunction with their marketing activity and better understand the incremental value, they are driving through channels and experimentation. This enables brands to strike a balance between acquiring new customers whilst sustaining profitable growth.
We’re also experiencing a resurgence in the interest of Marketing Mix Modelling (MMM) which provides brands with a framework to assess historical data to determine the impact of different marketing activities (e.g., advertising, pricing, promotions). This insight empowers brands to allocate budgets strategically, optimising for long term growth. This is an area both Google and Meta are investing heavily in, with Google launching Meridian earlier this year, its open source MMM tool.
Platforms that provide unbiased omni-channel analysis are gaining traction. Real-time attribution and comprehensive consumer journey analysis helping a number of brands improve customer acquisition costs, scale spending across channels, and make data-informed decisions.
AI and Automation
It has become key to do more with less personal data, creating value exchange through AI power rather than people behaviour. With this in mind, machine learning (ML) and AI are increasingly playing a huge role in success across our client mix.
New generative AI features are allowing brands to scale creative success more effectively with features such as background generation and image expansion across Meta.
Across Google, AI powered campaign types such as Performance Max and New Customer Acquisition goals help to maximise new customer conversion goals and drive greater value within a profitable target.
Conclusion
The evolving landscape demands a transition in how we are incorporating and looking at data within our marketing strategy.
An increasing focus towards first party and zero party data
Building a sound measurement framework and
Leaning into AI and machine learning
These are just a few of the ways in which brands are developing a data-driven approach, helping them to stay ahead of the curve, drive innovation and ultimately continued growth in an ever-changing digital ecosystem.
