8 types of audiences only offline data can uncover

You cannot read the minds of customers, but understanding their habits and behaviors is the next best thing. Tracing users’ digital steps is one thing, but to grasp the complete picture and anticipate what is likely to make them tick and stick, you need to take a look at real-life patterns. Offline data, consented to be shared by app users via location permission, is that vital piece of user knowledge that gives you 360-degree vision of your user base.

Audiences, built on the basis of data-informed user profiles, are at the core of your personalization strategy. You might want to communicate differently with a SoCal teenager or a London-based baby-boomer, we’re not teaching you anything new here. BUT, demographics and purchase behavior give you limited depth when it comes to audiences, particularly given that 90% of retail still happens offline, and in today’s “be relevant or die” ecosystem, no one can afford to just assume what these demographics require.

Here are some examples of offline-informed audiences which can take your marketing to another level:

Interest-based audiences

Part of an effective engagement strategy is playing into customer interests. Some you may know with relative conviction already (the likelihood that a running app user likes running when they do so every day is pretty high), but some take a little more digging for great results. Here are a few examples:

1. Fast food lovers 🍔🍟

You are what you eat? Maybe.
You buy what you eat?

Understanding the patterns of your user base lets you bring them just what tickles their taste buds. Figure out what types of places your customers tend to go to and treat them accordingly. This group of users regularly ends their Friday evening with a fast food run? Save the smoothie-maker ad for another audience, that 2-for-1 burger coupon is far more likely to get opens and to be redeemed.

2. Sports fans 🧘

Josh’s profile says he’s into sports. Fine. But there is a world between watching football from the couch on the weekend and religiously attending yoga classes before work. Even within the fitness community, picking out these yogis from gym bunnies or the bouldering fans will provide you with much finer, actionable audiences and drastically up the value of your communication efforts.

The type of places they visit is one dimension you should look at, the frequency is another. The frequency of their visits could qualify them for campaigns promoting different kinds of membership: a teen who visits the pool monthly with her friends will need a different kind of membership than an everyday line swimmer. Combined with your available demographic data, you can also add layers of product specificity depending on where these audiences live and their income bracket.

Such insights are what make you truly customer-centric and stay relevant.

Routine-based audiences

3. Commuters 🚂

For many, commuting constitutes a substantial portion of the day and any help making it faster or more pleasant is welcome. From a business perspective, there is value in understanding commute patterns and pinpointing the right time to engage to either provide relevant information or cashing in on the “bored on the train” or “sitting in traffic” window.

Is your user taking the 8 am train every weekday, and usually traveling back late in the evening? Travel updates during the afternoon peak hours are just irrelevant noise, as is the weekend 8 am train being delayed. A heads up that his usual evening train is delayed might save his day and secure you an appreciative user. Push out an offer for a cheap overnight hotel stay close-by for this late-night worker? Bingo.

Commute data is not only extremely relevant to travel-focused businesses. Think about the value of knowing what gas station is on your customer’s usual route so you can target them with specific offers or proactively surface a reminder to collect loyalty points? How about reaching out to users with items still sitting in the basket when they have 20 minutes to kill on their train journey?

Check out our eBook of moments to get some inspiration on more contextually-rich moments >>

4. Supermarket loyalists 🍓

Most of us are creatures of habit. One of the many routine destinations is the supermarket we tend to shop at most, either due to proximity, inventory, layout or even, who knows, that friendly cashier. Building audiences based on users’ favorite locations allows you to distribute (digitally or the old-fashioned way) your store-specific offers; cost-efficient, relevant, and ROI-boosting.

Insights into where users live/work and the locations they choose to visit also provide you with important store performance data. Why is it that users ignore this store right across the street and are willing to go the extra mile to shop at another franchise? You may want to look into what’s behind your customer’s choice, making sure you provide the best service across the board or cash out on the added value of specific locations.

5. Frequent flyers ✈️

Loyal users are a goldmine, a dream for improving customer lifetime value. However, many users have the potential to become loyal without you even knowing it. Picture this; how many travelers fly on a regular basis, only booking a fraction of their trips using your booking platform or online travel agency? These users are primed and tick all the boxes to become high value, loyal customers. Location history gives insights into untracked habits such as airport visits, down to destinations, visiting frequency, duration of visit, etc. This audience is worth investing in, and their behavioral data gives you all the personalization cues to reach out with the perfect content to get them converted and coming back.

In a nutshell: Frequent flyers that are not booking through the app = high potential audience

Read more about how an OTA generated x2 engagement by leveraging offline insights >>

Funnel-based audiences

6. Dormant Visitors 😴

Is it lack of opportunity or has your app simply slipped your user’s mind? For many loyalty program apps and mobile payment providers, users commonly find themselves in the optimal time and place, the app just isn’t top of mind enough to be actively made use of.

How many times have you walked out of a store only to realize you forgot to collect loyalty points, again? How often do your eyes stumble upon that forgotten app thinking “I should have used it back at that moment…”?

A quick query into location history data helps you isolate your dormant visitors from engaged deal-seekers or users who just aren’t visiting relevant locations. By uncovering this group of dormant visitors – you now have access to an audience that just needs a gentle reminder to turn into loyal users. When happy loyal users meet an app team who wants to serve them there-and-then, as well as keep them coming back? We call it a win-win-win.

7. Indecisive shoppers 🧐

Some of us are comfortable taking all steps of the purchase journey online, some of us not so much. I, for one, tend to go through a rather lengthy decision-making process, which often involves physically checking out the product. Sometimes multiple times. That is a behavior your online analytics wouldn’t pick up but puts me at a much different buying stage than if I had once visited a product page.

By leveraging offline data, keep an eye on me and my indecisive peers moving from online to offline and back. All this audience might need is a small push, the right offer, a ticking clock. Be more accurate in your estimation of a customer’s funnel stage, by starting to cash in on those opportunities to boost conversions and customer value.

8. Competition visitors 💏

Hey honey, wanna be exclusive?

You may have an extensive collection of data detailing the touchpoints between customers and your business. But can you tell what relationship they have with your competitor? Are you their constant go-to or their back-up plan? Are they upping their visits to competition and at risk of dropping you right when you thought you two were solid 😭? Like in any relationship, you need to be attentive, show them some affection, listen to their needs.

By looking at location history, not only do you have a complete overview of user interactions with your business, but also those with your competition. This data informs you, among other things, on the status of customer loyalty – are they qualified for a special loyalty program, or in need of a little extra love to win back their business?

Another more immediate opportunity, real-time location creates is that of geo-conquesting. This practice refers to reaching out to customers right at your competitor’s doorstep, immediately driving them out and back to your business. Recent winning case? Burger King’s latest geo-conquesting campaign showed impressive results by sending compelling deals to users entering McDonald’s. Now that’s great marketing.

Mix-n-match audiences

At the end of the day, the more refined your audience, the more personalized an experience you can provide them. By combining all the knowledge you have about users and crafting your strategy accordingly, you can work your way towards the winning combo of the right person, right place, right time, right offer. Ultimately, fine-tuning all the ingredients to achieve optimal results is a learning process; observe, try and learn, but start today!

Take a look at our collection of case studies and stories about how you can put offline audiences to work for your customers:

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