Retail Marketers Need To Get Back To Basics To Ensure Effectiveness
Retail success demands starting with the fundamental question - What is your value-based data exchange with customers? says MSQ's global chief data officer
10 November 2023
At MSQ, we’ve just finished an in-depth study into retail marketing. And if it wasn’t already clear beforehand, the interviews and insights shared show just how much of a daunting task retail marketers face.
There’s an ever-increasing array of channels. An ever-increasing to-do list. How are they balancing the way they measure their Amazon presence against their own site? How are they setting up their site testing, their CRO capabilities? How are they optimising their in-store activity? And that’s just the tip of the iceberg.
Most CMOs are probably aware that their teams aren’t set up in the right way. They have too many siloes – teams looking after affiliates who don’t talk to the team looking after the website… data teams who aren’t engaging with the content strategists, who aren’t engaging with those handling social commerce.
The easy (and unfortunately, correct) thing to say is that, from a measurement point of view, it’s critical to start optimising your commerce ecosystem holistically, rather than in these silos. There’s so much that can be gained from pulling it all together. What are the search patterns across your ecosystem? How can you combine your learnings with offline data, to start understanding your hyper localisation opportunities and tailor your messaging, pricing and promotions to different audience sets?
If it’s any consolation, I haven’t met a client team that’s got it holistically right yet. Many organisations are making strong steps forward, orchestrating the right teams, technologies and combining knowledge sets. But if you’re worried you’re the only ones who haven’t reached the holistic effectiveness view, you can ease up on yourself a little bit.
My first piece of advice here would be to at least step back and have a plan in place to make it happen. Speak to the right agencies, empower the right business leads and start coordinating where you can, importantly engaging data and technology as early in the process as possible.
And as you do that, my second piece of advice is to keep things simple. In the short and medium term, it’s about focusing on the fundamentals, with a shared agenda and orchestrating teams with defined goals in mind.
Getting the basics right
GDPR. The death of the cookie. “Reject all” tracking (with approx. 40 per cent + opt-out and growing YoY). Marketers face a tough time right now for digital commerce. And this will potentially become tougher as the increase in ease for opt out at a browser level, meaning you lose all digital analytics and behavioural data in a flash for consumers (unless they purchase).
These factors have naturally put the value of collecting first party data at an all-time high – hence why brands like Mars and Unilever have been working hard to set up their own direct-to-purchase set ups, allowing them to enhance their media and audience understanding in ways that won’t otherwise be as readily available as before.
But before you go chasing new workstreams or introduce new or refreshed loyalty schemes due to a focus on data collection, it’s so important you have the balance and ‘fundamentals’ in place first. What is your value-based data exchange with customers? Do you have the customer ‘must-haves’ in place – by which I mean the right pricing strategy, delivery options that meet consumer expectations and a strong level of service – before you then index on the ‘added value nice-to-haves’ – those extra rewards or surprise-and-delights that might be fun to implement, driver longer term loyalty and subscription and possibly even garner a bit of good PR? We see too many vibrant, content-rich loyalty programmes that could reap first-party data rewards but simply don’t have longevity because the business doesn’t hit the customer fundamentals in the first place.
The right help at the right time
Focusing on the fundamentals is a great result for your customers (value exchange) and a good message internally, too. By working with third parties to demystify your data, you can join-up and coordinate your learnings, distilling information in the right way so that it can be shared and optimised, empowering your teams, allowing them to build hypotheses into the creative, media, CRO and digital product backlog to test and continuously learn.
It's a really important first step – you won’t get the answers immediately, but it will set you on the right path for your strategists and creatives to develop those data-driven value exchange strategies. The aim here is to create a data driven Effectiveness Culture in the organisation that can then inform everything around your brand, from your storytelling to your data form collection, CX to your product development.
Of course, this can be done internally – but if you’re looking at what you keep in-house and what you outsource, it may save a significant chunk of time to benefit from an agency’s multi-client experience and additional technical capabilities, where test-and-learn strategies will have already been implemented and learned from.
We’re also seeing agencies benefit from MMM (market mix modelling) being talked about again as the ‘old new’ hero metric and being leveraged within the Google Analytics 4 (GA4) ecosystem. Brands of all sizes need a partner they can trust to help them navigate their complex measurement systems and leverage MMM, whilst not neglecting other realms of testing that will also proffer shorter-term goals. And is a must to have a flexible multi-measurement framework with a clear understanding of when to use, when to combine and when it is misleading across the teams, to fuel better data driven decisioning especially with the offline to online ecosystem.
So, whilst it’s very easy as marketers working in retail to get excited by new in-store experiences, marketplace innovations and the like, let the data guy calm things down a little. Cutting through the complexity and getting back to basics is fundamental to ensure you’re not just focusing on what’s hot, but what’s actually working too.
Amazon can wow us with facial recognition stores (there’s probably a whole other piece on what that means for the dangers of facial tracking and data security with Ai), but they can do that because they have the fundamentals – price, customer experience, data connectivity, value of data collection etc – down to a tee.
And I’m not saying you shouldn’t be experimenting, either. At MSQ we certainly make sure we keep innovating, keep testing, keep pushing the boundaries. But as the retail industry gets set for even bigger changes over the next decade, the real winners won’t be the ones who have grabbed a quick win using LLMs, they’ll be the ones who have a clear view of what’s driving their business, and how they can use the data at their disposal in the optimal way with a clear customer data value exchange.
Rob Goodwin is the global chief data officer of MSQ