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Rite Aid exec: Quick app technology, data offer predictive capabilities

rite aid

Rite Aid is leveraging data to simplify experiences internally and externally

NEW YORK – A Rite Aid executive at the NRF 105th Annual Convention & Expo affirmed that leveraging quick application technology to bolster internal business analysts’ and pharmacy technicians’ data insights is a smart strategy.

During the “Exhibitor BIG !deas: Understanding Your Customer Inside and Outside of Your Store” session, executives from Rite Aid and 1010data discussed the importance of consolidating differentiated data sets and category-specific reports to make them easily viewable via quick apps. The wellness chain also believes that big data will help predict which customers are most likely to abandon picking up their prescriptions, a feature that could one day be implemented into its mobile pharmacy app.

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“That’s something relatively new for us,” said Pete Bonnick, vice president of pharmacy services at Rite Aid.

Delving into data
Having differentiated data sets enables brands to enhance in-house analysis as well as scale apps more easily. Rite Aid partnered with 1010data to streamline collected data in a way that develops a one-stop shop for all pertinent information so that various departments, including finance and marketing, can easily access it.

“What we found is that you can go to three different people in the company and ask them a question, and get three different answers based on what database they use,” Mr. Bonnick said.

Streamlined data collection and presentation enables business analysts to become savvier, and helps brands better understand loyalty. In turn, this promotes more optimal creation of customer relationship management programs.


Equipping in-store employees with tablets is an optimal strategy

“It gives business analysts the right skill set,” Mr. Bonnick said.

Additionally, Rite Aid collaborated with 1010data on enhanced delivery technology. The companies layered in audio and graphs so that pharmacy technicians could have an easier job gleaning data while glancing at their personal devices.

Rite Aid has been working increasingly harder to ramp up its mobile offerings in the last year.

The chain targeted moms last Halloween on social media and through a mobile-optimized site where they could find tips, recipe ideas and other content for keeping on top of their busy schedules during the fall season (see story).

Spotlight on big data
Mr. Bonnick also posited that big data is shaping the future of pharmacy stores. Most notably, it will help predict prescription abandonment – a tactic that could significantly help maximize sales.

For example, if Rite Aid’s data informs the brand that a certain customer has not picked up his prescribed medication two times in a row, it could follow up with him by asking why he is abandoning his prescriptions.

Consequently, if it turns out to be a financial issue, Rite Aid can take the matter into its own hands and send a discount for the next prescription or refill. These types of targeted messages and programs could easily be rolled out via mobile to ensure the best customer response.


Consumers can easily manage prescriptions and refills via the Rite Aid mobile app

Another program that Rite Aid is considering is targeted immunization outreach. Big data will help pharmacy chains deduce which loyal customers have stopped in for their regular immunization shots, and which have yet to do so.

While these features are likely to fuel revenue for Rite Aid, they also contain components of corporate social responsibility where personal health and wellness are concerned.

The ability to churn out these types of tools on digital platforms rather quickly is another plus for marketers with a national presence.

“The steam at which you can turn things out is really beneficial,” Mr. Bonnick said.

Alex Samuely is staff writer on Mobile Marketer, New York. Reach her at alex@mobilemarketer.com.

 
Related content: Database/CRM, mobile, mobile marketing, rite aid, nrf, national retail federation, big show 2016, 1010data

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