3 ways to attract more customers and boost sales effectiveness

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Shoppers are growing harder to please every single day. Empowered with technology, they have far more options to choose from. Therefore, they jump from one retailer to another in a bid to get a better offer. Retail companies launch extremely deep promos to attract and retain customers. From my experience, in some industries like FMCG or giftware retailers cut prices by some 30 percent, while promo penetration can reach as much as 60 percent. It would be unfair to say that retailers do not grow their sales by doing so, because they do. But, sadly enough, improving sales do not necessarily mean a growing revenue.

The thing is that managers can rarely explain what was behind the decision to slash prices. Quite often, they tend to rely on their experience or are simply pushed by the changing market. But what if I said that retail businesses regardless of their vertical could make their pricing less subjective and, as a result, earn more?



Why don’t slashed prices and improved sales equal higher revenue?

When changing a regular or promo shelf price of a particular product, retailers inadvertently impact the revenue of the whole product portfolio. But they cannot estimate the magnitude of the impact and whether it is positive or negative. When it comes to calculating the right prices for thousands of products every week and factoring in hundreds of parameters (which seems inevitable in our tech-driven dynamic world), very often retail managers tap into impulsive pricing and alter prices without analyzing the effect of such a move. At least, for most products. This leads to retailers losing their revenue and, as a result, looking for new approaches to pricing.

To explain why I have chosen excessive promos and imbalanced prices as a starting point of this article, I’d like to cite two examples of real-world retail problems which our company has come across. A UK-based gift retailer Find Me a Gift (FMAG) used to reduce prices for a range of products blindly to attract more buyers during holidays. As the company was making 50 percent of its annual turnover in the run-up to Christmas, it seemed a reasonable move. However, growing sales did not translate into improving revenue. The retailer realized it wanted more. Let me quote Jean Grant, purchasing and product development senior manager for the company: “We were running around selling lots of stuff, but we wanted to find a way to make each pound work harder for us.”

Here is an example from the FMCG industry. Kosmo, a retailer operating across 100 price zones, had to deal with significant promo pressure, vendors dictating prices, and competitor-based pricing not only during holidays, but all the time. “It’s no secret that retailers and vendors use promos to stimulate financial performance. However, this leads to cutting prices non-stop. Everything has its limits, though. We were faced with a question of how to satisfy the customer while keeping the prices beneficial for the business. To do so, I believe, we needed to shift from price wars to predictive pricing,” stated Georgy Sheiko, the retailer’s CEO.

Now you can see: pricing is one of the levers which retailers use actively to entice customers (recent studies by Deloitte and PwC support this point of view). It desperately needs fixing. I’d like to suggest three approaches to doing that: consultancy, hiring a technological partner or building an in-house system.

Consultancy

Some retailers are fed up with rule-based pricing: they use rules created by pricing managers and converted into “if-then” formulas. Such retailers may ask a consultancy agency to come up with a pricing strategy for them. These strategies are usually well-prepared and useful, but crafting such a strategy takes a long time and costs a lot. Also, pricing strategies provided by consultants are rather long-term than short-term; they do not consider such factors as sales cannibalization and the demand elasticity of every product in the portfolio, as well as give no instruments to use for mass repricing campaigns.



Technological partnership

A growing number of companies realize that outsourcing everything else, except for what differentiates you from competitors, to a third party is a viable option. Inspired by the “fail fast” approach, companies partner with startups which are known for being passionate about what they do. Others, like MediaMarkt which has some 50 innovation projects annually, create startup labs to “grow” their own projects.

There exist third-party pricing solutions that help retailers optimize prices by using machine learning algorithms. They save retail businesses from engaging in developing and maintaining robust pricing systems. Such solutions provide data-driven price recommendations regarding any number of products for retailers of any size and evolve along with the needs and wants of retail companies in terms of the infrastructure and pricing models.

Retail “Samurai’s” Path

You are probably thinking: what’s he talking about? “Samurai” is my favorite nickname for those retailers that prefer doing everything by themselves; for example, in-house pricing systems, including those using machine learning. It works beautifully if you are ready to provide a lot of funding. Developing and maintaining such a system requires the engagement of an IT team, industry expertise, as well as constant financial support. Many retailers that design such systems independently from each other end up reinventing the wheel instead of using turn-key solutions available in the market.

The last two options revolve around machine learning algorithms. What makes them beneficial? When calculating prices, self-learning algorithms factor in thousands of latent relationships inside a portfolio to suggest individual prices that altogether maximize sales and revenue of the total product portfolio. Such algorithms can help pricing teams become more efficient which translates into increasing sales and revenue.

Meanwhile, speaking from my experience, pricing managers can be hesitant when it comes to applying price suggestions provided by machine learning algorithms (whether they are homegrown or brought from “outside”). It usually takes some time and significant financial improvements to break the ice. However, it works to the benefit of everyone. As an example, the market tests we held with some of our clients showed the following results: sales growth of up to 24 percent and a revenue boost of up to 16 percent, while managers were saved from routine tasks and got a chance to focus on tactical and strategic decisions.



All in all, I’d like to admit: optimal prices are not the only way to appeal to shoppers. Marketing, assortment, the overall commerce experience and dozens of other parameters are equally crucial for retailers. However, I’ve chosen pricing since imbalanced prices and promo wars were a big issue for our company’s clients. As we’ve accumulated some experience in dealing with such problems, I assumed that sharing it would help you tackle your challenges and grow your business.

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