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Why Your SMB Should Harness The Power of AI for Retail Sales Forecasting

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AI-driven sales forecasting can empower SMB retailers to meet demand, boost satisfaction, and drive results.

She hadn’t even planned to buy anything. Between leaving a client meeting and picking up her kids from school, however, she had a little bit of time, and the store was right there. She would be going out for date night at the end of the week, and she had seen a cute skirt the retailer showcased in an Instagram that had caught her eye.

Though the skirt is undoubtedly popular – she has seen friends and more than one perfect stranger on the street wearing one – there is an entire rack of them waiting for her when she walks through the doors. In fact, the rack is full enough that she is pretty confident they will have multiple shades in her size. Maybe it would make sense to buy more than one.

For a small or medium-sized business (SMB) like this fictitious retailer, the woman’s customer journey represents a critical moment.

It’s what could transform her from a casual customer who thinks of the small business as just one of many other retailers she may shop from, to a loyal customer who comes back time and time again because she trusts they will have what she wants in stock.

The availability of that inventory is the result of strong sales forecasting, and it makes the difference between a retailer that merely keeps its head above water during difficult economic times, and one that thrives.

Retail sales forecasting can be even more important for those customers who are not shopping for themselves. When the holidays get closer, harried parents may start to worry that the present they’d chosen for their child will be sold out.

In some cases, people are not coming to a retailer for luxury items or splurges, but necessities. This could include medical supplies like bandages, or replacement parts for an essential item that’s broken down. If customers see empty shelves, their disappointment can keep them from ever returning.

Despite its critical importance, sales forecasting has sometimes been treated more like an art than a science. Retailers might plan inventory levels based on what they sold the previous year, for instance, even though factors like weather or the economy can influence spending habits significantly.

Gut instinct has its place, but taking an educated guess is not reliable enough to ensure sales forecast accuracy. Then, when you do run out of in-demand products, you’re forced to order more and hope that your supply chain can work fast enough to meet your customers’ needs.

Artificial intelligence (AI) turns that reactive approach to sales forecasting on its head. By using historical data as well as models based on trend analyses and other inputs, SMBs can allow predictive algorithms to provide them with numbers they can trust.

AI isn’t necessarily intended to replace human beings who work in merchandising and assortment planning and contribute to (or lead) sales forecasting. Instead, AI and automation are tools that enhance forecasting accuracy and enable teams to exceed customer expectations while driving greater long-term loyalty.

The business case for AI in retail sales forecasting almost writes itself. Check out three key business benefits of AI below.

1. Data integration from multiple sources

SMBs that put their core data in a CRM are at an advantage when they use AI, because it allows machine learning (ML) applications to see the most critical details that indicate future demand levels. There’s no reason to stop there, though.

AI can also be used to build forecasts based on market data from external sources like research databases. It can come from feedback that customers directly provide to your SMB through surveys and other mechanisms. Even social media can help retailers (and AI) better understand what’s becoming a must-have item.

2. The ability to build customized models

Sales forecasts will never look the same all year long. Change is a constant within any business, and many of those changes will affect forces like supply and demand. Fortunately, AI can help take those changes into account.

A good example is peak buying seasons. Besides obvious moments like the holidays, retailers might see a shopping surge as a new product comes to market, or even when they release an upgraded version of an existing product. Products that tie in with pop culture moments like movies and TV shows can affect buying, too.

For other SMBs, there might be value in creating customized models based on particular customer segments. If young professional men aged 18-24 represent your biggest spenders, for instance, you could use AI to get insights into their expected purchases for a particular quarter.

3. Real-time execution

Developing a sales forecast shouldn’t be like writing a book report in elementary school. Too often, however, SMBs have had to take time out to pull whatever data is on hand, study it, make their best estimates, and prepare the final numbers for distribution.

AI doesn’t just make this process faster and easier. It also ensures that all the data which gets put into a sales forecast reflects how shoppers are behaving right now. This makes it a lot easier to be more responsive to what customers want, and it can be done with much larger volumes of data than employees could manage on their own.

The future of AI-based retail sales forecasts

Retails need comprehensive sales forecasts to achieve their growth targets. The good thing about AI is that it doesn’t treat each forecast like an isolated project.

In fact, SMBs that use AI for sales forecasting over time will discover how the right tool will learn about the nuances of their businesses. That means their ability to meet customer demand will only get better and better.

Sales forecasting is key to your customer experience because it covers off a basic need – that shoppers can get what they want when they want it. AI is the best way to develop forecasts that deliver. 

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