Omnichannel Analytics Best Practices (2020)

Omnichannel Analytics Best Practices (2020)

We’ve been talking about this for a while, and now retailers are feeling it; major retailers are shuttering stores, a global pandemic is changing the way people are shopping, and global supply chains are rapidly transforming.

The bottom line is this:

Consumer behavior and expectations have changed — and will continue to do so into the 2020s.

So how can retailers use omnichannel analytics to reconnect with their customers?

While this a deeper question that can’t be answered completely in a single article, today we’ll focus on how predictive analytics can convert your data into tangible actions, build a consistent customer journey, and allow you to stay agile and flexible enough for such a dynamic reality in multi-channel retailing.

 

Converting Omnichannel Retail Data into Tangible Insights

 

According to Accenture & Forrester Research, 71% of shoppers said they expect to view in-store inventory online, while 50% expect to buy products online and pick them up in a store of their choice. With COVID-19, these numbers are only bound to increase. Unfortunately this is still a major disconnect between consumers and retailers as the Annual Supply Chain Benchmark Survey pointed out, 62% of retailers said inventory visibility was very important, but only 39% said the process was complete or even in progress.

Interestingly, it’s not data collection that’s the problem anymore. The ability to collect sales, inventory, and loyalty data has never been easier and more flexible. Today retailers have access to online/social loyalty programs, RFID, interactive digital displays in stores, beacon technology, mobile POS, traffic cameras, and much more.

So what are retailers missing that is keeping them from becoming data-driven and using their insights to take tangible actions that reflect consumer expectations?

According to the survey, the top challenges that stood in way were:

  • Lack of a coordinated, unified demand forecast across all channels;
  • Lack of real-time inventory visibility up and down the supply chain, including the stores;
  • Lack of effective forecasting and replenishment with vendors; and
  • Lack of organizational alignment and business rules for compensation/incentives by channel.

Moreover, the same survey found that while 84% of retailers utilize dashboards & scorecards to monitor performance against business goals, 56% of them feel that they are not using these tools effectively.

So what’s the real challenge at hand? The answer is truly a integrated retail predictive analytics strategy and platform. Consider the following:

Existing business intelligence tools and traditional analytics software are ineffective for making decisions going forward. These tools are not able to account for new products, categories, and markets, or used & exchanged items, let alone suggest accurate and tangible actions going forward.  If there is one constant in retail is that nothing ever stays the same. Therefore driving your business while looking in the back mirror only ensures that you will continue to make the same mistakes in the future.

Many analytics vendors claim that their software supports multi-channel retailing, and yes, what they mean is that they will provide analytics for each of your channels, leaving you to manually consolidate and unify the results for your whole business. This is a common mistake. How are we different? Well for starters, Retalon’s integrated predictive analytics solution collects data from all possible sources, intelligently removes dozens influencing factors (i.e. seasonality, price-elasticity, geo-demographic diversity, past promotions) and applies sophisticated mathematics to your specific business rules, policies, and costs constraints — cross-channel.

Only after aligning the math with your business as a whole which results in a significantly more accurate forecast the results are re-applied to each channel.  (Eg. Replenishment results are optimizes with promotional forecasts automatically) In this way, the retailer is able to continue doing business with optimal synergy between each channel, decreasing inventory costs, boosting sales, and creating a truly consistent experience for your customers. Here are more reasons why Retalon’s Predictive Analytics is the perfect fit for Retailers.

 

Building a Truly Seamless Customer Experience

 

In an Annual Supply Chain Benchmark Survey conducted by Boston Retail Partners, the group found that more than 62% of retailer respondents indicated providing a seamless customer experience is a top company initiative.

Retailers are working hard to get as close as possible to their customers, by reaching them wherever they are. Opening new stores can be expensive and risky, which is why many retailers have began connecting with their customers through Facebook, mobile apps, e-commerce stores, and pop-up/kiosk locations. However, the more touch points a retailer creates, the more difficult it is to forecast demand, allocate inventory and provide shoppers with consistent prices, promotions, and inventory levels in real time.

Retalon allows retailers to stay a step ahead of their customers. Equally importantly a predictive analytic solution can be easily scaled as a retailer grows, or adds and removes sales channels. For example Follett, a University book store with over 900 locations and 4 million SKUs (due to the sheer volume of textbooks) experiences a surge of sales the week before the school year. They use predictive analytics to optimize several billion store/SKU combination very quickly.

 

Using Analytics to Preempt Customer Behavior

 

Arguably the world’s greatest heavyweight boxer of all time, Muhammad Ali, once famously said at a press conference: “I’m so fast that last night I turned off the light switch in my hotel room and was in bed before the room was dark.”

Predictive analytics assures you that your product will be at the right place & time and the best price before your customer gets there.

If scalability is important as retailers attempt to build stronger connections with customers, the ability to react faster to shifting demand in-season and increased supply chain risks is key. Customers have unprecedented ability to search and review any products they’d like to buy with more options open to them than ever before. Ultimately many retailers will often compete on the fulfillment strategy. The more convenient of an experience they offer a customer, the bigger chance they will turn them into a loyal member of their brand.

A Forrester research team surveyed retailers on what they plan to implement to support fulfillment efforts. Here’s what they said:

  • Buy via mobile or web site in-store, pick up in-store (64%);
  • Buy online, pick up in-store (62%);
  • Buy via mobile or web site in-store, ship to home (60%);
  • Buy online, return to store (50%); and
  • Buy in-store, return to another store (46%).

 

This dynamic fulfillment approach isn’t just the reality of where retailers need to be today, but it is also highly profitable. For example, the ability to provide a more convenient experience for a customer can results in larger basket value. According to Adam Silverman, a principal analyst at Forrester Research those retailers that that adopt ship from store programs “can drive a 15% to 30% lift in online sales.”

The challenge that many retailers are having is that even if they planned well and allocated merchandise correctly, a busy season, or special promotion can create inventory & assortment distortion in some stores, or DC’s. Once retailers notice overstocks, or excess lose sales due to out-of-stocks they begin to react. Usually by purchasing more inventory they already have in other locations, or marking down inventory that is selling too slow.

Predictive analytics makes adopting strategies like ship-from-store a breeze. The system will proactively monitor your demand, inventory levels sales, promotions, associated costs and dozens of other factors and suggest only the most profitable in-season inventory transfers. This effectively reduces unnecessary transfers, purchases, or markdowns, and instead balances assortment across all channels and locations, and sells slow moving products at locations/channels that have demand for them at full price. Here’s more detail on how Retalon’s Inter-store inventory & assortment balancing process works.

Instead of looking at technology as a threat to retailers, these companies should look to technology to take their business to the next level. Understanding customer demand and creating a consistence customer experience begins with a unified and powerful predictive analytics approach — whether you’re dealing with a complex, multiple channel fulfillment strategy, or need to improve the performance of your offline channels. The sooner retailers will adopt this technology the sooner they will begin to see improvements in their bottom and top lines.

Get in touch with us to get an analytic assessment of your business though Retalon’s Predictive Analytics Platform at discover@retalon.com

 

BIO


Yan Krupnik is the Business Development Manager at Retalon, the world’s leading provider of Predictive Analytics for retailers. Since 2002 Retalon has optimized pricing, inventory management, merchandising, planning, and marketing operations for retail organizations in a variety of industries. Retalon products range from task-oriented solutions to a common analytic platform, resulting in tangible optimization of the supply chain and significant measurable benefits for the entire organization.