{"id":24819,"date":"2022-12-20T18:54:44","date_gmt":"2022-12-20T18:54:44","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/20\/first-party-data-strategies-for-2023-retail-media-loyalty\/"},"modified":"2022-12-20T18:54:44","modified_gmt":"2022-12-20T18:54:44","slug":"first-party-data-strategies-for-2023-retail-media-loyalty","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/12\/20\/first-party-data-strategies-for-2023-retail-media-loyalty\/","title":{"rendered":"First-Party Data Strategies for 2023 Retail Media Loyalty"},"content":{"rendered":"

<\/a>\n<\/p>\n

\n

One of retail media\u2019s biggest selling points has been the robust first-party data<\/a> the retailer has gathered from customers\u2014their buying habits, brand affinity, purchase frequency, price sensitivity and even flavor or color preferences.\u00a0<\/p>\n

The richness of the data depends on how meticulous the retailer has been collecting and slicing that information over\u2014well, in many cases, decades. Retailers set their own prices and definitions of premium CPC, CPM or access fee on that data, package it up and sell it to brands. Sure, that\u2019s not the only major value<\/a> retail media offers, but it is a biggie.\u00a0<\/p>\n

Retailers collect this information in a myriad of ways, ranging from payment methods, logins and apps. But the most common way to tie it all together across devices and locations is a loyalty program<\/a>.<\/p>\n

And the reason why loyalty programs should matter so much to you as an advertiser? Well, this is part of the proof that the size and strength of their first-party data is as good as they say it is. For the advertiser, it can open up a wealth of opportunities, such as identifying new-to-brand customers, look-alikes, repeat purchasers and people in the market for your type of product\u2014whether they\u2019re closer to conversion or just getting started on their research journeys.\u00a0<\/p>\n

\n
\n
\n
\"image\" <\/source><\/source><\/picture><\/a><\/div>\n<\/section>\n<\/div><\/div>\n

A retailer\u2019s first-party data is only as good as their collection methodology when it comes to placing value on the media activations that the first-party data powers. We\u2019re currently on the verge of being able to make some very interesting comparisons between retailers or determinations about how much \u201cvalue\u201d that data actually has. As I think we can agree today\u2014not all first-party data is created equal.<\/p>\n

One of the biggest mistakes retailers make today working with marketers is not providing transparency into the collection methodology, strength and segmentation capabilities of their loyalty programs. What I need to know is how your first-party data will make my new-to-brand customer dreams come true.<\/p>\n

So let\u2019s take a deeper look at the types of loyalty programs that power most retail media offerings today and you tell me\u2014who\u2019s got a loop that\u2019s actually closed? And how about some retail media trivia: Who created the first modern loyalty program and in what year? Answer is at the end\u2014stay with me!<\/p>\n

Paid versus free<\/strong><\/h4>\n

The ability for retailers to segment out paid versus free loyalty audiences will be a huge deal for marketers. Some examples of paid loyalty programs are Walmart+, Kroger Boost, CVS CarePass and Best Buy Totaltech. We have several retailers now with paid subscription-type member models (outside of Amazon Prime) that are not currently segmenting or making readily available customers in these audience buckets as an option.\u00a0<\/p>\n

Conversely, there are some free loyalty programs that are doing a great job of collecting first-party data and have made available some more nuanced audience segments. This includes Ulta Beauty<\/a>, Target and Kroger. The ability to target different levels of membership, gift registry receivers and givers, and audience affinities, like flavor profiles, is bolstered by their continued investment and engagement in their programs.<\/p>\n

And they also don\u2019t call them customers but are more likely to refer to these loyalists as guests, shoppers or beauty enthusiasts, a badge of honor which creates a strong sense of community, which in turn makes for some strong first-party data collection opportunities. Also, consider that both Target and Ulta have their own credit cards with additional benefits for members.\u00a0<\/p>\n

No loyalty program?<\/strong><\/h4>\n

Perhaps surprisingly to some, Walmart, America\u2019s largest retailer, does not have a loyalty program. They have the paid Walmart+ membership but are staying close to their original everyday low pricing business model, which makes sense. But this also makes it more difficult to close that loop on first-party data, especially with such a heavy emphasis on in-store purchases that can also be paid in cash, SNAP, EBT or other untrackable tenders.<\/p>\n

If the customer has the Walmart App, pays with a credit card or uses one of their many services or partnerships like cash-back app company Ibotta, that can help strengthen data collection. What gets missed in first-party data, they definitely make up for in spades in scale\u20144,700 stores and millions of in-store and online visitors a week.<\/p>\n

The Home Depot and Lowe\u2019s don\u2019t have loyalty programs either. But they have professional trade options with Xtra Pro and Lowe\u2019s for Pros programs, but those are not for the everyday DIY type of customer. (They do have credit cards, though.)\u00a0<\/p>\n

In these cases, it means marketers must ask questions about first-party data collection methodology and match rates as a percentage for the campaigns when comparing online media to in-store sales and average order value size. This may help you connect the dots to credit card sales over cash and how tightly that loop really did close.\u00a0<\/p>\n

How to test first-party data strength<\/strong><\/h4>\n

Ah, the million-dollar question as we go into fiscal 2023 planning. Here are a few tips based on the assumption that you\u2019ve run or tried at least two marketing campaigns or some self-service options that have audience-targeting capabilities:<\/p>\n

Review your brand\u2019s 2022 performance as a whole.<\/strong> Bucket the audiences you targeted by retailer with the associated spend and see what your percentage was by audience. How much of your total went to retargeting, like lapsed purchasers? Or how much went to narrower audiences, like customers who bought during a retailer-specific event like Baby Month?<\/p>\n

While you\u2019re at it, throw in some average CPMs. That\u2019ll give you a nice dashboard of how much a CPM at one retailer compares to another. You might also find you had some bargains in there to repeat in 2023.<\/p>\n

Determine whether to go narrower or go wider.<\/strong> If the majority of the audiences fall within low-hanging or templated media plans and the performance was meh, then you know you need to shift to a narrower category. But be sure to add in a variable, like in-market, and shorten the time frame. Or pull back on some of that contextual and try something else.<\/p>\n

Ask about custom audiences and loyalty program segments.<\/strong> Be specific and creative. Retailers often have their own events, like Ulta\u2019s Fall Haul, or moments like Target\u2019s indoor allergy month. There are also usually specific offers for FSA funds at the end of the healthcare plan year. That\u2019s a good place and time to target narrower (and hopefully more in-market) at a larger scale due to the additional promotion around it.<\/p>\n

Dig into opportunities around tentpole sales events.<\/strong> There were three or so major shopping \u201cholidays\u201d this year: Prime Day<\/a> (summer), Prime Savings Event, Walmart+ Rollbacks and Cyber 5 (Thanksgiving through Cyber Monday). Maybe you don\u2019t want the three-times-a-year bargain hunter to be included in your next campaign because of their limited lifetime value, or maybe you do.<\/p>\n

\n
\n
\n
\"image\" <\/source><\/source><\/picture><\/a><\/div>\n<\/section>\n<\/div><\/div>\n

Is all first-party data created equal? No, some is better than others. But they\u2019re all definitely more valuable than a crumbling cookie. <\/p>\n

P.S. American Airlines in 1981.<\/p>\n<\/p><\/div>\n