The Evolution of Retail Sales Strategies

The retail landscape as a whole is growing, evolving, and streamlining. In particular, the growing importance of e-commerce today has led to a new wave of growth in retail. Adapting to new technological innovations and general market trends is essential if retailers are to remain competitive in the modern marketplace.

In the past, it was reasonably difficult to accurately optimize various aspects of a company's sales strategy. Things like profitable marketing, dynamic pricing, and brand loyalty are now closer to a science than the relative guessing game of the past. Artificial intelligence plays a huge role in this ever-changing environment, allowing retailers to make the most of every little detail.

Competitive prices.

E-commerce and online shopping provide consumers with great price transparency as they can compare the best prices for a product within minutes. A 2014 Forrester Consulting study found that 81% of US shoppers compare prices between different vendors before making a decision (you can learn how price sensitivity is measured here). This shift in consumer power is forcing merchants to adapt daily, if not hourly, to their competition. After all, being squeezed by competing retailers on a regular basis does not bode well for a company's longevity.

Before competitive pricing became a cornerstone of the retail industry, the process of evaluating competitive pricing was fairly simple. Manually checking and adjusting prices, while a fairly simple task, can quickly become time-consuming and inadequate to compete with things like brand loyalty and promotional pricing. Now, more than ever, technology is heavily relied upon to fill this gap and do it effectively.

Competitive data scrapers and web crawlers are one-way retailers that can gain a complete picture of their competitors' strategies without any effort. They can efficiently generate comprehensive price and activity reports for a specific product in minutes, allowing businesses to monitor not only their direct competitors but also any retailer selling similar products. Some competitive data software can also be integrated with corporate goals and rules, allowing more pricing data to be presented and reviewed for overall pricing decisions.

Much of a retailer's business can be attributed to attractive and well-timed promotions. Smart marketing and competitive discounts can leave a lasting impression on shoppers and go a long way in growing retailers: the holy grail of brand loyalty. As a result, monitoring competitors' promotional strategies provides a more transparent view, while optimizing their own promotions helps retailers fight price wars with as little profit as possible.

This evolving, data-driven landscape highlights some previously unimaginable aspects of retail. The need to constantly stay competitive with pricing strategies forces companies to change their pricing in incredible ways. In 2013, Amazon was already changing its prices 2.5 million times a day, more than its major competitors.

Overall, while dynamic pricing may weigh on retailers in their mission to remain competitive, today's consumers benefit. While virtually every major retailer tries to entice shoppers with their prices, consumers are now more empowered than ever.

The growing importance of consumers

As consumers are now more empowered with a wider choice of prices and suppliers, their importance is reflected in retailers' business strategies. Instead of trying to sell a product to as many buyers as possible, it's now about getting the most value from a single customer. While some data-driven marketing strategies may seem cumbersome, they certainly go a long way in building customer loyalty.

If you've ever bought anything on Amazon, you've seen personalized recommendations or a "People Also Bought..." tab on virtually every product page. But instead of guessing. They show you what their algorithms think you're most likely to buy. Similarly, if you are an active member of an online marketplace, you may receive emails or messages containing recommendations for future purchases. By completely reducing product discovery time, it can be easier for e-tailers to build brand loyalty through personalized recommendations.

Targeted advertising is a highly visible application for retailers (and websites as a whole) to "get to know" their customers. By analyzing users' browsing behavior, search history, and personal information, the algorithms behind online advertising deliver ads that are more likely to interest them.

On the other hand, promotions can also be personalized. One such example is custom discounts for items in a customer's cart or wish list. This approach is designed to increase conversion of all wish list items and increase customer loyalty through a personalized offer. On a smaller scale, a personalized discounter groups shoppers with similar interests or characteristics and offers each group a promotion tailored to their needs.

The Role of artificial intelligence

Overall, the explosion of data over the past decade has fueled the development of technologies that can make sense of it all. AI plays a huge role in today's market primarily in the collection and analysis of large-scale data. All of the above strategies have been greatly enhanced and enhanced by AI, be it competitive pricing or targeted advertising.

The truth is, people don't have time to meet and get to know each of their clients. However, analyzing millions of bits of data daily with machine learning tools is the next best thing. The use of AI in retail is increasing as more retailers begin to understand the value of these tools. Whether their goal is to reduce costs, increase brand loyalty, or better execute a company's mission, AI is always there as a data-driven assistant.

There are many applications of artificial intelligence not covered here, many aimed at improving retailer-consumer relationships. Smart chatbots, email marketing, personalizing the customer's product experience (think Netflix's recommendation algorithm) and more are changing the customer's retail experience.

The widespread digitalization of the retail industry has given consumers more options than ever before, and retailers have started implementing machine learning tools to survive in an increasingly competitive environment. While it may sound like a strange conclusion, artificial intelligence, of all things, has helped retailers better understand their customer base.

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