Using Zero Party Data At First Contact Beats An Upsell On The Metrics That Matter

Many brands still waste the first message a customer ever receives. They collect zero-party data at signup, a birthday or a pet's name, then send a welcome message that ignores all of it. The follow-through is where it breaks, and a generic greeting burns a brand's single best moment of attention.

Carla J. Donahue, Senior Director of Lifecycle at WITHIN, has built her career on that follow-through. The integrated creative and media agency builds media and lifecycle programs for retail and consumer brands including The North Face, Ben & Jerry’s, and Revlon. Before joining WITHIN, Donahue built her experience in beauty retail and owned media at JCPenney. She reads multi-touch customer journeys with an operator's attention to what each message costs and earns.

"Your first post-purchase communication should not be asking the customer to buy more," Donahue says. A message should earn its place by serving the customer, whether it greets them or thanks them. Most brands agree with that in principle, but far fewer execute it, which is where the trouble starts.

Why personalization stalls

For all the money brands pour into data capture, the execution lags well behind. Donahue sees the same disconnect across companies that have the right inputs but lack a clear way to act on them. "Personalization is messy because everyone knows it's important and collects the data, but they don't know how to use it. The confusion comes from not integrating your systems properly, and from not knowing how to execute against the information you have," she says.

Some of that is structural. Marketing stacks have grown through acquisition for years, with larger platforms absorbing smaller tools and stitching them together, and the seams tend to show. A preference captured in one system rarely passes cleanly to the one that sends the email or the text, so the signal a customer gave dies in the gap between them. The rest is habit. Teams that have never had to operationalize zero-party data default to the broad sends they have always run, treating personalization as a setting to switch on when it takes steady work to build. Closing the distance requires making the existing systems talk, and giving someone the job of acting on what they say.

AI reads, people reason

Increasingly, that job falls to AI, which handles its part well. The problem is what teams stop doing once it takes over. "AI's biggest strength is also its biggest risk. It can build silos inside a single company, because teams outsource the critical thinking to it and stop talking to each other. That is where the gaps show up," Donahue says.

Her team builds a dedicated model for each client, fed with that account's full history, and aims it at the reporting most teams never get through. One pattern it keeps finding is how differently customers behave by channel, down to which categories sell through email and which move over text. It catches that in time to act on, which a manual pull rarely does.

"We use AI as a third business partner to validate some of our hunches by using the data," she adds. The model is one input among many. The decisions belong to the people who answer for them, which works only when those people are in the same room.

Who's in the room

The fix is a smaller room. Donahue keeps the group deliberately tight, built from people who can both decide and execute. "If you take a director and an executor from each department and have equal representation from merchandising, site, paid, and owned media, that small group can really get a lot done. You can do a lot with eight people who represent the four biggest pillars of your company," Donahue says.

The pairing matters as much as the size. A director sets direction, and an executor knows what can be built, so decisions made in the room hold up when they leave it. The four pillars cover the customer's whole path, which is what lets the group catch handoffs that fall apart when teams plan in isolation. At WITHIN, that shows up in how lifecycle and media work together, with email and SMS signals fed back to platforms like Meta so paid and owned don’t bid for customers the brand already owns.

Playing the long game

Donahue does not ask customers for everything at once. Progressive profiling lets a brand gather intelligence as trust builds, one small question at a time. "Asking a customer for all their information upfront is off-putting, so we build up to it. For a pet food brand, that might mean starting with what kind of pets you have, then learning their names, then their ages. Once we know you have an older dog, we can recommend food for their joints," she says.

Each answer shapes the next message and opens the door to the next question, so the profile fills in without the customer feeling interrogated. The payoff arrives as predictive pacing, where a single purchase signals what someone will need months later. WITHIN's Grow with Me series for The North Face maps children's apparel to how fast kids grow. A purchase in the 12-month size cues the 18-month message before the parent thinks to look, and a separate cohort flow keeps those customers clear of offers that contradict where they sit in the cycle.

That kind of timing only works if the automation behind it stays current. "If you're not revamping all of your flows and automations every six months, you're doing it wrong," she says. Behavior shifts with the calendar, and a flow tuned for winter delivery rarely fits a summer of in-store pickup. WITHIN runs an always-on testing approach, holding a test in market for six months with a holdout group alongside it to measure incrementality and confirm what moves the needle. The team never tests more than two variables at once, which keeps the read clean enough to act on.

Beyond the push

Donahue sees easy wins in the messaging channel that most brands leave on the table. Keyword opt-ins are the first. "Brands don't use keyword opt-ins and keyword texting as much as they should. If you can have multiple keywords for signup, it gives you an understanding of what the environment is," she says.

The same hesitation shows up with richer formats, usually over cost. Donahue sees that as a missed chance with the customers most likely to buy. "A lot of brands are afraid of MMS because they cost a lot of money, but the ability of MMS to show colorways, sizes, and also the multiple categories that you sell is invaluable. Using MMS to a select group of high-value or likely-to-purchase customers can be impactful," she says.

Donahue expects Rich Communication Services to give text and email the visual pull of social. Getting there depends on a clean connection between the customer data and the channel. "As long as you have all of the data collected at a contact level, then you're going to be able to do the same things that you can in an app where you can do customized push notifications, you can show individual products through images, you can show video. It's just going to come down to people being bold enough to test into it and then take those results and redirect dollars," she says.

Thank you first

The moment that tests a brand's discipline most comes right after checkout. The first message should thank the customer before it sells anything. Donahue’s team has run it against the usual review request and upsell across several brands, and the thank-you comes out ahead on the metrics that matter. "A reminder of easy free returns, which a lot of brands are hesitant to talk about, creates a lot of trust and value with the consumer. With one client, we saw triple the click-through rates on those emails. Those customers also went to buy about one time more per year, because the message felt less like a promotion and more like a  thank you," she says.

What ties Donahue's approach together is a long view of the customer, where every message either builds the relationship or spends it. None of it is specific to pets or children's apparel or any one vertical, which is why she keeps pointing brands toward the category she thinks does it best. "Everybody has something to learn from beauty, because it's the category doing personalization best. Most of what works there carries straight over to a furniture, shoe, or sunglasses brand," she says.

The views and opinions expressed are those of Carla J. Donahue and do not represent the official policy or position of any organization.