What does it take to persuade more shoppers to visit brick-and-mortar stores in the digital age? Let’s consider the following scenario:
I am a somewhat regular customer at a local juice shop—I have their app on my phone, I participate in their loyalty program, and I am even eligible for a free drink. However, my schedule has been hectic recently, and picking up a glass of healthy juice has not been a priority. Today, I get a push notification from the shop saying:
Chances are, this message will catch my attention and persuade me to plan a stop at the juice shop the next time I am in the area. That’s because it’s not a general message sent to all juice shop customers—it is personalized for me. It speaks to my loyalty status, my preferences, and my history as a customer.
This level of personalization is a powerful motivator, especially when it is delivered strategically for maximum customer influence. For example, what would happen if I received this notification while running errands near the juice shop? That’s even better! I am much more likely to stop in if it is convenient for me to do so. And once I enter the shop, what if they push me a follow-up mobile notification for a great deal on a dozen chocolate mini-donuts instead of just one? Now they’ve really got me—at the right time, in the right place, and with the right message that is personalized to me. Now let’s explore how they’ve done it.
As consumers move their purchases online for more choices, better prices, flexibility and convenience, businesses that want to increase their in-store traffic have to do more than just display products and run price promotions. Even giant retailers like Walmart have been seeing footfall traffic declines for many consecutive quarters, and this trend applies equally to restaurants and convenience stores as well. If these businesses want to bring consumers back through their doors, they must, like my local juice shop, up the ante on the level of personalization they use to engage and interact with their customers.
This means going beyond inserting customers’ first names in emails or showing certain content on the website; it requires a real-time awareness of each customer’s:
Combined, these factors create complete context for each customer. Consider the power of real-time customer context in the following scenario:
I am browsing through leggings and trousers online. My favorite brand takes notice, and immediately pushes me a notification while I am still visiting their site:
An understanding of my context—including my current browsing activity, past transactions, and loyalty status—empowers the brand to deliver the message that is most likely to resonate with me in that exact moment.
Keep in mind, however, that context is not static. I might be browsing a company’s website on my smartphone one minute; I could be driving by their store the next. The ability to access all of a customer’s most up-to-date contextual data points at any given time is what enables brands to deploy hyper-personalized interactions—and when your goal is to increase and optimize in-store traffic, location is the name of the game.
While ecommerce and mobile devices are seen as the main causes of lagging store traffic, smart retailers are embracing mobility as part of today’s omni-channel shopping experience.
For instance, Nordstrom recently announced that it is using location-based ads on Facebook to help drive in-store traffic. Similarly, other retailers are exploring the use of analytics and proximity technologies such as geofencing, iBeacons, and WiFi tags to trigger personalized, location-based recommendations. Businesses can even guide customers to in-store departments that house products of interest—which is how my juice shop deployed a deal for my favorite donuts as soon as I entered their store. Consider this even more targeted scenario:
I walk into a department store to pick up a dress I have ordered online. When I step foot inside the store, I receive a mobile notification with a map that guides me to the pick-up counter. As I make my way through the store, I also pass by the handbag section. Immediately, I receive an alert:
Instead of fighting online retail, this brand is leveraging my ecommerce activity to get to know me better, and then using this personal knowledge to determine how best to influence my in-store behavior.
The technology that supports this level of influential personalization is a new stack; a new generation of systems that can enable an enterprise to touch every customer in a hyper-personalized manner at scale.
Machine Learning (ML) is at the heart of such personalized engagement. ML ensures that as the system ingests more and more customer data, it is able to learn and act on customer affinity and intent. These AI-powered tools then go on to determine a ‘zone of influence’ for each customer, or a situation in which the probability of a transaction is the highest. Once the influence zone has been determined, the most appropriate and relevant action is triggered—a personalized message, offer, or notification for the customer.
The possibilities of ML/AI-driven use cases in such a scenario are endless. Let’s revisit my local juice shop to see how they could leverage customer influence zones to drive in-store traffic:
It’s the hottest day of the year, and I am on my way to cool off at a local pool near one of the juice shop’s locations that is different from my typical stop. The temperature is nearing 100° as I approach the shopping center where the juice shop is located. To my delight, I see a message pop up on my phone:
Now this will certainly make me tap on the directions and head towards the store! By learning from my past brand interactions, determining my current influence zone, and deploying a message designed to resonate with me, the brand has effectively gained my loyalty—and my in-store business.
The ZineOne Customer Engagement Hub enables large enterprises to incentivize in-store traffic by understanding and responding in real-time to individual customer activity, solving the challenge of personalized engagement at scale.