Rewiring The Future Of Retail Merchandising With Analytics

Last Updated : 23-February-2024

The retail industry is witnessing a paradigm shift. Fast-pacing technologies, changing customer expectations, and emerging digital organizations are driving widespread disruption. Clearly, from a plethora of markets, new products, and customer segments to the burgeoning expansion of marketing and sales channels (like mobile and social commerce), retail is at a tipping point.

In the current scenario, customers are now demanding rich shopping experiences that are personalized, hyper-connected, and engaging. Moreover, numerous forces are revolutionizing the landscape: the explosion of data and connected devices, cloud technology, and more. This makes it crucial for retailers to showcase agile tech adoption and business process optimization.

Retailers today operate in an environment of relentless volumes of data. To succeed, they must capitalize on advanced data and analytics to transform their merchandising. However, certain challenges remain in place, which include- siloed applications, lack of business models, and the inability to deploy the latest technologies. This impedes the delivery of a seamless, omnichannel shopping experience. To overcome these hurdles and future-proof businesses, a robust and end-to-end strategy is the need of the hour.

Until recently, numerous retailers could win with a clear value proposition, as long as merchandising understood the promotion effectiveness, articulated a decent pricing strategy, and had a process at their disposal to review its chainwide assortment. Presently, that’s no longer enough. Consumers now need retailers to make things easy for them, with personalized offers, localized assortments, a speedy shopping experience, sustainable sourcing and new product segments. To win, retailers are required to deliver all of this—along with real-time price adjustments and integration with third-party online marketplaces.

Currently, numerous merchandisers are ill-equipped to handle this complexity. Some of them still rely primarily on excel spreadsheets, manual processes, and gut instinct. They house data in multiple silos & run ad hoc processes resulting in lagging reports, disconnected, which means they are unable to run tests or make data-driven assortment decisions.

Various retailers recognize that they need to do better, and a number of them have already made investments in advanced analytics. More often, the gains are incremental, unsustainable, or both. For instance, one grocery chain that relied too heavily on analytics actually saw a downfall in sales growth, which organization attributed to algorithms killing off too many promotions in an attempt to enhance gross margins.

So, the underlying issue is that analytics is often treated as a black box: something that retailers turn on and then wait for the correct answer to emerge. A matter of fact is, analytics is an extremely powerful tool—and like all tools, it can be less or more effective and that depends on how it is handled. And to make the most out of analytics, organizations should go after an integrated approach.

A key roadblock is that retailers often lack an integrated approach to advanced analytics. If the operations, technology, and underlying algorithms all come together to reinforce one another, it can give the organizations a differentiating benefit. Retailers that try to have advanced analytics as a solution, instead of taking an integrated approach, often experience “glitches” as the merchant team struggles to unlock value from the torrent of data now available to them.

The out-of-the-box solutions force merchants to make too many low-value changes to their processes, while customized options need too much change and compromise too quickly.

A survey with some retailers shows that about 70% of the effort and focus in implementing analytics should be devoted to organizational factors: ways of working, the strategy, processes, skills, and capabilities—and how changes to those elements can curate a benefit. Another 20% should address enabling technology: swift, scalable solutions that deliver the right decision analytics and recommendations, on-demand and often in real-time, in a simple, and easy format. And the remaining 10% should make investments on tuning the algorithms.

In the present scenario, top retailers apply an integrated process with a crystal clear objective to offer merchants more accountability and information to deliver better customer outcomes and scalable decisions faster across a set of practical, actionable use cases.

Brand Management

With the continually changing consumer preferences and dynamic market, the way a brand perceives itself and the way it is being perceived by the consumers can differ to some extent. Organizations can use retail merchandising analytics solutions to get an accurate picture of their present brand equity. They can understand patterns and market trends to see their position among the competitors through the eyes of their consumers. The branding and marketing team can derive data-driven insights to identify the issues and rectify them. They can make optimized strategies to enhance brand image and induce customer loyalty.

Share On Shelf Space

The retail shelf is one of the main consumer touchpoints and also one of the most competitive places when it comes to sharing. With the increasing competition, new product lines coming regularly, and dynamic consumer trends, brand representatives are required to work hard to maintain and occupy shelf space. Organizations can utilize merchandising analytics to find the consumer inclination towards their organization and increasing sales percentage, and persuade store managers to offer enhanced location and space for a specific product.

Recognizing Opportunities, Market, And Product Gaps

As retail stores catering the demands of a broader consumer market, the offerings can be unsatisfactory to many customers. The informed customers of today have specific needs, demands, and require personalized services and products to satisfy. Businesses can use retail merchandising analytics solutions to derive valuable insights using external data such as- market trends and social sentiments, and internal data from all channels. They can rectify product gaps, specific requirements and offer personalized offerings via private labels. This will assist retailers to stay a step ahead of their rivals in this ultra-competitive retail space.

A Personalized And Localized Approach

The customers are becoming demanding, and even more personalized services and products coming every passing day. This can make it tedious for big retail chains to keep up with this without utilizing analytics. Regional stores being more responsive, flexible, and knowing the typical customer demand, can customize their services as per convenience. Top retailers can now offer personalized services and highly localized assortments using advanced merchandising analytics. Retailers can take out predictive insights related to emerging demands, consumer trends and align their offerings in a perfect way to increase conversions and improve customer satisfaction.

Dynamic Online And In-Store Pricing

Today, most customers tend to research the final purchase. Retailers can utilize analytics to generate data-driven insights to experience real-time recommendations and dynamic pricing. For online channels, it is simple to implement these insights, but modern retailers can also use the advantages of dynamic pricing through electronic shelf labels. Retailers, mainly from fashion, can utilize merchandising analytics to optimize markdowns by predicting potential demand and aligning it with inventory to minimize losses.

What does success look like? It is believed that the merchandising function of the future will have three features, with data and analytics underpinning all three:

It Will Be Genuinely Customer-Led

Top-notch retailers will have a relentless drive to localize, personalize, and curate the offer to keep customers happy. They will spend substantial time understanding broader trends and consumer needs in their segment. Each product category will be optimized to what customers value most across all dimensions: availability, product value, consumer choice, and other attributes. SKUs and brands that deliver on customer needs and financial metrics will be prioritized; those that do not deliver will lose their place in the assortment.

Merchandisers Will Be Able To Do More

Insights and tools will be integrated into processes, authorizing teams to make data-driven decisions rather than over-relying on experience and instincts. A robust link will exist between strategy, decisions, and outcomes. Automated tools will take over the load of day-to-day activities like- ad planning and promotion or small changes to the assortment, with sheer efficiency and effectiveness. That will make teams spend more time on higher-value activities, like- localizing and personalizing products, curating assortments, and services, and collaborating with supplier partners to deliver solid products at lower prices. Teams will also be more smart and responsive to changes in the market, able to identify and implement changes more rapidly.

The Performance Will Improve Every Day

The last feature will be a culture of continuous improvement on two levels. First, the retailer will capture customers from feedback and supply chain partners, along with sales performance, and rapidly adjust to improve its offer continually. Second, the organization itself will constantly improve in areas such as faster innovation, more convenience for customers, & keeping costs low. Processes and new tools will be kept simple for the initial rollout, with additional capabilities added over time.

At Polestar Solutions, we've a team of highly experienced industry experts, architects and motivated individuals with incredible knowledge to deliver seamless strategy & services for your organization. We have developed industry-leading solutions for multiple Fortune 500 Clients. Book a session with our professionals experts today to know more about retail merchandising analytics.