How Retailers Can Fast Track AI Adoption with a Testing Lab

By Vipul Goyal, Product Manager

Physical retailers have long endured a strategic disadvantage to their online counterparts due to lack of data (just look at the statistics.) To stay competitive, physical retailers must harness the power of data in order to measure customer behavior.

Ecommerce Solutions in a Physical Retail Setting?

More exciting artificial intelligence (AI) systems are giving physical retailers the advantages digital competitors enjoy through the use of AI-driven computer vision and automation platforms.

Emerging AI/machine language (ML) solutions in physical retail include:
Personalized marketing.
Customer behavior monitoring.
Incident detection.
Stock monitoring.
Loss prevention.
And countless other in-store automations.

Hope (and Help) on the Horizon

Companies are finally adopting these opportunities to realize greater growth and operational potential while setting themselves apart from the competition. Unfortunately, this growth is being thwarted by a reluctance to adopt and leverage AI.

Why the hesitance? It’s the “What ifs”:

What if we have the wrong hypothesis?
What if testing disrupts our day-to-day operations?
What if delays drag on for months or YEARS?
What if the data is collected/interpreted wrong?
What if the costs run over?
What if the final output isn’t actionable in real life?
What if we don’t know what to do next?

What-ifs turn some retailers away from the very AI/ML solutions that would close the gap between competitors and ensure long term growth — growth fueled by useful customer data.

Radio Shack and the Consequences of Poor Data

How can history show us the perils of customer assumptions based on little to no data? Radio Shack is a good place to start.

In the late 90’s and Early 2000’s Radio Shack tried to pivot from their hobbyist roots. Leadership was following the crowd and attempting to compete with the likes of Best Buy and Amazon. In an effort to keep up with the crowd, Radio Shack shifted their floor plans to focus on selling cell phones, hoping to attract a new customer base. What Radio Shack failed to see/understand, was that their customer base was do-it-yourselfers all along.

If they’d had access to useful customer data and today’s AI solution, they might have pivoted to meet the needs of the emerging maker revolution of the 2000s. Just one historical example of what can happen without clean, clear, relevant data.

The good news is, this isn’t the 2000’s, and retailers can leverage new AI solutions to avert avoidable missteps.

A simple customer tracking software could save you a fortune in spillage and theft. Another AI tool could tell you, “Nobody has gone down Aisle Four in months.” Yet, many retailers are still willingly falling victim to organized retail crime, internal liabilities, employee theft, and failure to understand their customers. Any one of which could be the difference between leading the competition and being eliminated from it.

Why the reluctance to adopt the very tools that could help?

Why Are Retailers Reluctant to Leverage AI?

Put simply, cost and risk. What risks? What costs? They include:

Unavailability of clean Integrated data— Too many companies fuel AI/ML projects with the data they can easily collect using the tools they have on-hand. If teams aim to develop powerful, scalable, future-proof AI, with market growth potential, they need data of the highest quality. Failure to do so means poor performance, poor audience representation, loss of market adoption, and diminishing hope of growth success.
Lack of rapid prototyping facilities representing data reality — Proof of concept is critical to launching development. But how long will a POC take? Where will the testing be done? Who’s monitoring the data, collecting the data, analyzing the data? With rapid prototyping and expert analysis, teams can uncover hidden obstacles in customer journeys. Such an approach allows them to recognize real-life edge cases before they become a problem.

Assumptions lead to unclear next steps, frantic version 2.0 adjustments, and damaged go-to-market strategies. All of which mean costly delays and a big bite out of the bottom line.

How the Studio by Centific Can Help

Imagine a highly customizable testing lab where retailers can build floor layouts, shelving, points-of-sale, and more. They can test ideas at reduced (and highly optimized) cost, turn-around time, and risk. The Studio provides the technology, space, and expert teams needed to achieve proof of concept in one place over just 12 weeks.

The Studio provides:

End-to-end data collection and labelling services.
Reduction of total cost of ownership of AI/ML.
Our proven, global, and state-of-the-art expertise in applied AI.
Our ever-expanding network of tech partnerships to lend complementary assets.
Our suite of proprietary apps, solutions & platforms to amplify your outcomes.

The Studio ensures the highest quality and accuracy while providing real (and often unexpected) insights into customer journeys and behavior. Our data-driven approach provides teams with:

Actionable ROI plans.
Strategic product roadmaps.
Architecture and infrastructure blueprints.
Data quality assessments.
And more to enable teams to execute their strategies with confidence.

Winning in the retail world can feel like a massive challenge. But by leveraging the right data and properly tested AI/ML solutions, retailers can accelerate innovation, craft more meaningful customer experiences, and enable a more predictable, data-driven future in the physical retail world.

If you’d like to learn more, contact us.