February 22, 2021 • 6 min read
Walk around Manhattan for a weekend and you’ll notice that a handful of brands have storefronts all over the island. The Upper East Side location may be smaller and have a more minimal selection, the SoHo store might be massive, and perhaps it’s difficult to find things in the Midtown location.
They’re all the same brand, though, and customers’ experiences at each store front will influence the way they feel about the company as a whole.
As brands strive to understand how they are perceived, it’s crucial to recognize how in-store experiences differ between locations. Sales data, point-of-sale data, and anecdotal evidence are valuable, but they don’t provide the entire picture.
Enter Location-Based Intelligence (LBI): text analytics technology that pulls information from the social web and provides spatial and temporal insight into the thoughts and feelings of customers.
Here are six examples of industries whose members could benefit from using Location-Based Intelligence.
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Companies that seem to have a brick-and-mortar store on every street corner in Manhattan, like Starbucks and McDonald’s, are tasked with understanding how the customer experience differs between each storefront.
With LBI, the company could see that a particular branch has notoriously long waits during the morning rush (as evidenced by angry social media posts), and that customers orders are messed up more often at another (ditto).
These insights could spur a staff increase at certain hours or a reassessment of the workflow to ensure customers get what they ordered, and quickly.
To take it further, if one location is providing incredible experiences, then the manager could train managers at nearby stores that aren’t performing as well.
Take a hotel brand with many branches across the northeast. A location-based solution would help the company identify differences in the customer experience based not just on location, but also on time of day.
It would allow the brand understand if people are having better experiences checking in at night compared to the morning. LBI would also arm management to better know when they tend to be understaffed, if there’s a cleanliness problem, or if rooms aren’t ready on time.
If a certain branch is drawing an inordinate amount of social chatter about grubby sheets, the brand would have the power to see that quickly — and more importantly — act on it efficiently.
Imagine a national, big-box retailer with brick and mortar stores in numerous cities. In a place like Manhattan, there are four storefronts within a five mile radius of one another. They’re different sizes and offer a slightly different selection depending on the local clientele.
A store like this could use LBI to understand how the customer experience differs at each store, and what drives loyalty of customers on an in-store level.
Perhaps customer service is stellar at one store, where people often tweet about how helpful the sales reps were in helping them find the right sizes. Another might be lacking on the customer service front, but is home to fewer Facebook posts about items that are out of stock.
Large retail brands often have many brick and mortar stores in a single city or region, and only by understanding exactly what’s going on in each store can they know how to optimize the customer experience at each one.
It’s not just huge product related corporations that can tap into the power of location insights. It also holds opportunities for smaller, growing businesses like medical providers that rely heavily on the quality of their in-person service.
With LBI, such companies can tap into reviews on Yelp to uncover pain points like billing issues and problems with specific providers.
Take a popular dental practice with more than 500 offices across the country – and plenty of customer feedback on Google Places, Yelp, Facebook and consumer review sites. The operation can benefit from understanding the quality of its customer experience across all locations, and how they compare to one another.
Imagine someone has to renew her license at the DMV (fun, right?). She waits in line for what feels like an hour, but when she finally gets to the counter, she has a downright pleasant interaction with the DMV employee.
She writes about the experience on Google reviews, mentioning that the wait was rough but noting that the employee was friendly and helpful.
Alternatively, maybe she didn’t have to wait for a very long time, but the renewal process was confusing and frustrating. Again, she reviews accordingly.
What if the DMV could take this feedback and use it for good? Using a location-based solution, it could examine criticism and compliments online, attribute them to specific locations, and act on the feedback to improve experiences for customers across the state-wide offices.
Since online banking is quickly growing in popularity, there’s a major premium placed on in-branch experiences.
LBI allows banks to understand where the customer experience falls short, and ultimately create a better process for helping customers.
Additionally, the technology can help banks anticipate and solve major issues before they turn into crises. Imagine that at a particular branch, customers are tweeting because they feel the bank is being biased in its decision not to approve loans.
In a case like this, LBI could help the bank recognize the negative sentiment on social, help connect the dots back to that particular branch, and even uncover if customers feel most frustrated at a certain time of day.
At that point, the bank could take steps to correct the situation through implicit bias training or other measures. Ultimately, LBI can give the bank the power to make sure that all customers feel they’re being treated equally.
Just about any company with multiple storefront locations can benefit from an Location-Based Intelligence solution.
Not only does it allow brands to understand the in-store customer experience better than ever before, it provides the means to gather location-specific, actionable insights, to keep improving goods and services in tandem with the needs and wants of customers, and track progress over time to ensure that the customer experience is always improving.
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