In a nutshell:
- Many businesses are still in the early stages of meaningful online personalization
- Low login rates create a major barrier to gathering the data needed for tailored experiences
- Consumers expect relevance, but their willingness to share data is shrinking
- Simple, behaviour-based techniques can still deliver value without heavy tech or third-party tools
- The best results often come from combining digital personalisation with real-world, human insight
The challenge
Personalization has been a buzzword for years, but delivering it well (especially online) is still proving elusive. The idea is simple: create a more relevant, seamless customer experience. The reality is more complicated.
One of the biggest hurdles is data. Without enough logged-in users, it’s difficult to gather reliable behavioral signals. In some businesses, fewer than 10% of users are logged in while browsing, making it hard to tailor content, make useful recommendations, or track what’s working.
At the same time, consumers are more cautious about what data they share. The desire for personalized experiences hasn’t gone away, but the willingness to hand over email addresses, accept tracking, or stay logged in has dropped sharply. This creates a tricky paradox: people want relevance, but are reluctant to enable it.
Then there’s the question of what actually works. In gifting-led journeys or big-ticket purchases like TVs or sofas, customer behavior is sporadic and hard to predict. The standard “you bought X, now try Y” logic doesn’t always apply, and when purchase frequency is low, even small increases in retention or cross-category shopping become hard to measure.
What are Hive members doing?
Hive members are tackling this challenge in a number of ways.
Some are focusing on the fundamentals, like encouraging logged-in behaviour through perks like personalized discounts or app-only experiences. When users are logged in, the uplift in engagement is noticeable. Even getting someone to make a second or third purchase in a year, especially from a new category, can dramatically increase lifetime value. The trick is finding the right incentive to prompt that behaviour in the first place.
Others are bypassing the data question altogether by using anonymous behavioural signals. Personalizing a homepage based on what someone viewed on their last visit, without relying on logins or AI, can be surprisingly effective. A simple server-side script can identify which categories a user spent time in and tweak their experience accordingly. It’s low-tech, but it works.
In physical retail environments, human interaction still wins. When store teams are trained to capture data conversationally, rather than pushing forms, opt-in rates can reach 60% or even 100%. The timing matters: too early feels intrusive, too late and the moment’s gone. The best-performing stores treat it like choreography, not a script.
Some businesses are experimenting with hybrid approaches. Using store apps that allow associates to tailor the experience in real time, or applying insights from in-store behaviour to digital journeys. For example, matching online recommendations to how people shop sensory-led categories like fragrance or food—areas where scent, sound and texture shape the decision-making process.
For others, the challenge is technical. Getting different data systems to talk to each other, working within GDPR constraints (particularly across regions), or making sense of the mountain of product-level data that exists in trade-heavy categories.
And in all of this, there’s a growing focus on value exchange. Making it clear to customers why logging in or sharing their preferences will result in a better experience, rather than just another cookie banner or generic prompt. Some members are starting to experiment with clearer messaging and opt-ins that explain what’s in it for the customer.
The next steps
1. Start with the behavior you can see. Even without a login, track things like visit order, category depth, or time on page. These can inform homepage content, recs or email segmentation.
2. Nudge, don’t force. Encourage login or app use by showing tangible benefits, like personalized offers, a smoother checkout, or early access. Make the exchange feel worthwhile.
3. Don’t over-engineer. Personalization doesn’t need to be complex to be useful. Sometimes a small tweak, like surfacing a related product or remembering a user’s last search, is enough.
4. Blend human and digital. Look at what’s working in store and ask how that could be reflected online, whether it’s tone of voice, timing, or journey structure.
5. Focus on like-for-like groups. If individual behavior is hard to predict, think about clusters; how do new parents, first-time buyers or seasonal shoppers behave as groups?
6. Build trust, not just data. Be transparent about how data is used and what customers gain from it. If people trust the outcome, they’re more likely to opt in.
Want to know more?
Reach out to PJ Utsi, Co-Founder & Chief Creative Officer, directly at [email protected]
