What is retail analytics and how can it inform your data-driven ecommerce merchandising strategy?

There is such tremendous activity both on and off of retailer websites today that it would be impossible to make smart merchandising decisions without powerful analytics.

Sometimes in-store trends precede online trends and sometimes it’s the other way around. Omnichannel sellers can leverage trends in social or mobile to inform their business or inventory strategy. Businesses that offer buy online, pick up in store (BOPIS), social sellers, and live online sellers have even more data to crunch.

In the age of AI, being able to analyze data should be getting infinitely easier, but ecommerce has become very complex, and it can be tough for an online merchandiser to know where to start. That’s why we’ve put together this guide to help merchandisers make sense of their analytics options.

What is retail analytics?

Retail analytics utilizes software to make sense of information from data sources such as websites, mobile apps, and retail stores, including details of customer journeys across categories, the status of inventory, what’s going on with the supply chain, and what the balance sheet is looking like.

Or, as Oracle puts it, “Retail analytics uses empirical data and science to make decisions in what traditionally has been an intuition-led field.”

Where do retail analytics get the troves of data needed to come up with insightful analysis? From analytics software such as point-of-sale systems that track customer behavior and buying on a website, among other places.

How can this technological wizardry, which often incorporates machine learning, translate into optimization of your business operations? With the right analytics insights, a company can:

  • Accurately forecast customer demand
  • Better manage inventory, keeping just enough stock on hand
  • Help management make data-driven decisions that hit pricing sweet spots
  • Get actionable insights on what individual shoppers and groups of people want
  • Pinpoint browsing and buying patterns
  • Raise customer satisfaction levels
  • Discern customer loyalty levels
  • Optimize staffing
  • Optimize the ways items are laid out in physical stores
  • Better target marketing campaigns to align with prospects’ interests

How can retailers leverage analytics?

By gaining access to data-driven insights on consumer behavior, a retailer can then streamline how they merchandise and other aspects of their business. In short, having access to advanced analytics means being able to make the business decisions that create the functionality of a better customer experience.

Types of analytics

Among the types of analytics, predictive and prescriptive are two you’ll want to understand.

Predictive analytics

Predictive analytics allows a retailer to see into the crystal ball and project demand by assessing variables — seasonal considerations, what’s going on with the economy, what competitors are doing. When an ecommerce site’s management team can gain valuable insights regarding emerging market trends and demands, they can align to improve customer satisfaction and increase conversions.

Prescriptive analytics

While predictive is about seeing the future, prescriptive is about the best ways to respond. When it’s clear why you’d want to move in a certain direction, and you can confirm that in real time, as the numbers evolve, you can confidently embrace a response. For example, Let’s say you have a shopper talking to your chatbot. If you have prescriptive analytics on board, the bot could intuitively suggest a product or next steps to the prospective customer based on how the conversation is going.

How analytics can improve retail merchandising

data-driven merchandising banner

Want to gain a competitive advantage? Retail analytics can help you:

Track shopper journeys

In the new omnichannel world, it’s impossible to know exactly where a prospective customer will start engaging with your brand and then possibly either purchase or abandon their quest for an item. That means retailers must have all the bases covered, whether you’re talking about a solid social-media presence, attractive physical store layout, or inviting website.

Retail analytics can give you in-depth detail on how people navigate from, say, your app to your physical store to pick up an order. When you’re aware of this pattern, you might, for instance, want to launch a promotion that would encourage more people to try this method of buying.

Better manage your inventory

Have you been wanting to streamline your business-process efficiency so you don’t over- or understock?

For many retailers, the top business expense is maintaining the right inventory levels, as inadequate inventory management has been found to cost retailers in the billions.

You can use predictive analytics to avoid making inventory mistakes, such as not restocking in time. Or thanks to your customer data, you might have a chance to adjust the amount of inventory you keep in a particular location based on your shoppers’ changing buying patterns, thereby eliminating excess items and the costs that go with storing them.

Set the right pricing

You can use retail analytics to set up dynamic pricing (both online and with in-store shelf price indicators) and recommendations in real time. Predictive analytics is a great tool for optimizing markdowns through assessing demand and matching it with inventory.

Keep your shelves full

Have you ever lost sales because an item was out of stock and nobody realized it and no shoppers said anything? The shelf-space replenishment issue is a disaster that retail analytics can help you avert. In real time, merchandising analytics can alert companies about stockouts and allow you to automatically correct problems.

Improve your marketing

Retail analytics can illuminate a variety of areas for focusing marketing efforts. Do you know how well a current marketing campaign is performing? Retail analytics can reveal issues that may be getting in the way of better metrics. Perhaps your data could reveal an interesting online-shopper habit, such as people’s common gravitation to a certain page, making it a no-brainer for your merch team to place a banner there.

Skip the guesswork

With the right analytics tools for your retail business, you can clearly understand your customer preferences, streamline your physical store layout, make suggestions on your website that are likely to resonate with your shoppers, and make data-driven omnichannel changes to support a considerably more impressive bottom line.

How can you start using retail analytics to increase profit? One bet is to team with Algolia to upgrade your search and discovery for an improved customer experience. We’re here when you’re ready to take charge.

About the authorCatherine Dee

Catherine Dee

Search and Discovery writer

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