Data and mobile proximity marketing: Analytics optimize real-time communications

By James O'Brien

| Retail

Mobile proximity marketing is about offering the right deal at the most relevant moment. Fifty-three percent of customers are willing to allow retailers to track their location via mobile device if it means they’ll receive relevant offers, according to the Marketing Technology Blog.

Of the companies polled in a 2015 CMO report, 41 percent said mobile proximity marketing through SMS would be part of their strategy to drive conversions throughout the year. A significant next step in this expanding frontier of mobile engagement is to add real-time data analytics to the mix.

With the advantages that data can deliver — namely, predictions based on past behaviors and the ability to fine-tune offers according to consumers’ wants and needs — the following methods put the power of location and timing in every chief marketing officer’s palm.

Beacon Technology: A Data-Gathering Network

It’s easy to use beacon technology as a trigger for offers when consumers enter a given space. But beacons in the physical-store ecosystem are actually gathering all kinds of valuable marketing information, too.

From the paths consumers take through a store, to how long they pause at a display and the items they select within that context, data analytics add behavior analysis to a marketing team’s toolkit. CMOs need to take advantage of the two-way flow of data in the beacon space, capturing what beacons collect in addition to leveraging the messages they can send to customers.

Data Analytics Contextualize Beacon-Based Offers

Consider the following example of how mobile proximity marketing works in highly personal ways. Say a beacon notes a customer is in a location where weather data predicts an impending, sudden downpour. It sends the shopper an alert about the rain and offers a voucher on a nearby store’s selection of umbrellas. Alternatively, it could send a weather alert and suggest ducking out of the rain for lunch, including a voucher to a nearby restaurant.

In either of these situations, the marketing team has just engaged in what Retail Store Analytics refers to as micro-location marketing strategies. Beacons make this type of strategy possible, and real-time analytics mixed with consumer, weather and inventory data make the tactic highly personal and relevant. When it comes to customers and the proximity marketing strategy, it’s a win-win.

Data-Driven Proximity Marketing Means Relevance at All Levels

As data identifies segments and niches within a business’s customer base, beacons can trigger activations to entire demographics across a given geography. In other words, the offer doesn’t have to be tied to a rainstorm. The strategy can be as simple as identifying consumers who bought running sneakers six months ago and, when a member of that segment approaches a sporting goods store, offering them a loyal-customer discount on a replacement pair.

It’s the data-driven narrative that makes this offer especially attractive. The customer’s prior brand experience is acknowledged and rewarded with a reasonable proposal: that the customer’s shoes are six months old and that experts at Livestrong recommend replacing running shoes twice per year. To sweeten the offer, the consumer gets the proposed product at a price break. He is in the right place, and it’s an offer that fits within the context of his running routine.

A key takeaway to these considerations is as follows: Reach consumers with a timely opportunity to save or discover something new — a product or service that’s aligned with their wants and needs — and they’ll welcome proximity-based outreach. Put data analytics to work in amplifying that effort, and CMOs can improve outcomes, boost conversions and earn customer loyalty, one location-based offer at a time.

Written By

James O'Brien

Technology Reporter

For the past half decade, James O'Brien has covered technology and the ways it intersects with our lives and work. His points of focus include data analytics, the mobile sector, driver-less cars, the Internet of Things, IT infrastructure, data security, 3-D printing, and technology…

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