Everyone’s telling marketers they need to add AI to their madtech stacks. But fools rush in, says Jess Simpson, head of strategy and analytics at Acxiom. To stand any chance of making AI or any tech investment a success, you need to get your data management layer right first.
Cannes is over, and after countless keynotes, panel discussions, and Rosé-cooler conversations, the results are in: everyone says marketers should be using artificial intelligence (AI), but no one’s exactly sure how to use it – or how to prepare for it. And I believe this gap will be one of the most dangerous traps for brands in the coming year.
Don’t get me wrong, AI is going to do amazing things for your marketing. But instead of jumping straight into the latest flashy tech and tools, you have to get serious about your data and identity strategy first.
Because here’s the part no AI guru is saying out loud: a lot of madtech is commoditized, whether AI-driven or otherwise. What’s not commoditized is your relationships with your customers and the intelligence you can build about them as individuals.
You can have multi-channel platforms ready to go, with AI to power your segmentation and creative strategies, but it’s only going to go so far if you haven’t done the work to understand your customers.
So, allow me to bring you back from the glitz of Cannes Lions’ madtech innovation to the unglamorous-but-absolutely-critical data practices you need to get right if you want to make use of AI.
Firm up your data foundations
When I say data foundation, I’m talking about all the ways in which your brand gathers, manages, and uses customer information – and how you connect it to the real individuals behind the data, to engage them in intelligent, ethical ways.
A data foundation helps you meet customers’ desire to see deeper value. Perhaps you’re trying to reach parents, for example. Don’t just offer them a discount voucher. With a greater understanding of their key stressors, concerns, and interests surrounding children and parenting, you can help them understand how your brand is going to help them navigate parenthood. There’s a powerful difference between a customer thinking they can save a couple of bucks on diapers, and believing your brand can support them as they raise their child.
It’s a complex marketing blueprint as unique as a fingerprint, but you should start building it today – or risk having a very hard time down the line.
Here are four steps to get you started.
1. Optimize your data collection
You’d be surprised how many brands don’t have a grasp on exactly what customer data they’re collecting, where they’re collecting it, and how. So start by auditing and updating those practices. Work backward from what you want to understand about your customers if you know. (It’s also okay if you don’t yet know what you need to understand about your customers, so long as you understand what that means for your data collection strategy.)
Are you building consent into your data strategy? Are you giving customers access to the data you have about them via a preference center so they can review everything, update or remove information, or make other requests?
By giving customers control over their data, you can actually end up learning more about them. And an open, transparent interaction like this can contribute to a positive customer experience. Remember, data collection isn’t just the housekeeping around the experience – it’s part of the experience. And that’s only going to get more important in a cookieless world.
It’s worth stressing the importance of a data minimization strategy focused solely on what you actually need to create truly meaningful customer experiences, without always having to rely on personally identifiable information. All your customer interactions then become more relevant – whether you’re talking to existing customers when they visit your website, or to an unknown lookalike audience in a paid advertising environment. You’re much more likely to convert from these deeper connections than more superficial personalization at scale. (And it will help you earn the trust of your customers when it comes to the ethical use of data about them.)
2. Don’t neglect data organization
Brands I work with often have data located in between 50 and 100 places – and that’s just the smaller ones. With big, global CPG groups, the numbers can make you dizzy. So simply consolidating all that data to get a view of your data set becomes a significant job – let alone processing it into audience segments.
This is foundational work that can be fast-tracked with the help of intelligent automation. The tricky part is that the way this kind of automation is evolving – think data science and AI-powered classification – means it very quickly becomes something mere mortal marketing managers will struggle with. So you need an expert team.
3. Get the right talent in place
The exact mix of data and analytics skills you’ll need in your team will depend on the sophistication and scope of your marketing plan, but a strong technical leader will always be a critical appointment. They can help break down the walls between leadership, product, marketing, and analytics teams.
And with an experienced view of the hugely complex madtech landscape, they can help to steer your technology investments to meet your marketing needs. Importantly, they can also map those investments to the internal talent that will need to manage it and the partners that can help you succeed – identifying gaps to be filled along the way by hiring or co-creating solutions with partners.
4. Put the data to work on priority use cases
Finally, you’re ready to put your data to work. And if you’ve followed the steps I’ve outlined so far, you can be confident you’ve got a reliable data management foundation in place.
Start by identifying the use cases you’re confident will deliver real value, and be deliberate about defining that value up front, along with timelines for when you aim to see it delivered.
The key here is to set expectations based on your capabilities today. You might have a senior-level stakeholder in sales hoping for great things from AI, but if you’re not aligned on the value that’s expected versus the resources you have in place in terms of people, processes, and technology, you’re headed to trouble down the line.
Do the hard work now, so everything’s easier later
I warned you this stuff was unglamorous. But without a robust data and identity strategy in place, none of the amazing outcomes promised by AI-powered madtech innovations are possible. I’m not here to rain on any parades – just to remind you to put in the hard work now, so that everything becomes easier later.
Maybe it’s because I’ve had Cannes on my mind, but for me, the data strategy conversation reminds me of moving to a new country. It’s really exciting to think about the beauty, the landscape, and where you’re going to live. The hard part is learning the language. It’s not the nice, Instagrammable part – but it’s the part that’ll determine whether your move is a long-term success.
Learn how Acxiom’s data management solutions can help you lay the foundations for AI and other madtech innovations, so you can acquire, grow, and retain the customer relationships that matter most.
