Twitter
Facebook
Linked In
RSS
Login or Register
New to InternetRetailing?
Register Now
Internet Retailing
You are in: > Home > Views > Guest Comment

This is your 1 complimentary article for this month

Become a member for unlimited and immediate access.


Register
Already a member? Log in here

GUEST COMMENT How gift retail uses AI price optimization software to appeal to customers and increase revenue

Linked InTwitterFacebookeCard
Sharelines

GUEST COMMENT How gift retail uses AI price optimization software to appeal to customers and increase revenue

Vladimir Kuchkanov is a pricing solutions architect at Competera
Vladimir Kuchkanov is a pricing solutions architect at Competera

What stands between gift retail companies and their profitable future in the £1 billion UK market? Probably, “the death of the high street” calling for the necessity to innovate and reimagine traditional approaches to various business processes, including pricing, the need to create a single commerce experience across all selling channels, and Brexit. The list may go on. However, the main challenge is the need to change quickly and adequately.

A “fail fast” attitude is in the air. Advanced gift retailers are open to trying out and understanding the impact of technology like AI in many areas, including pricing.

What are the main price-related challenges of UK gift retail?

Balanced prices remain a weak point for most retailers. Many gift retail businesses have thousands of products under management — and just a team of pricing managers to handle everything, if they are lucky. In many cases, one person oversees every single thing. At the same time, the UK gifts market is extremely dynamic and calls for near real-time reaction to price changes. New prices need to be balanced, which means they do not irritate customers, improve marginality, and factor in different reaction of different products to price changes. Bear in mind that by modifying a shelf price for a product, retailers inevitably change the revenue and profit of the whole product category. To make sure they set optimal prices, retail managers need to consider various pricing and non-pricing factors when calculating prices. Unfortunately, retail teams usually have neither time, nor the computational capacity to make all the necessary calculations. As a result, they set optimal prices for the best and worst-performing items, while the rest of the assortment keeps inadequate prices.

Another Achilles heel of today’s gift retail pricing is the constant need to launch promotional campaigns. Customers are used to deep promos in gift retail. To tailor to their expectations, retailers may offer a 30% discount for a group of items and increase sales significantly, especially before holidays or during Black Friday. Holidays are the time when gift retailers make as much as 56% of their annual profit. However, retail teams very rarely calculate the impact of such price changes on the total revenue of the whole product portfolio. Also, it is well-known that boosted sales do not necessarily convert into a growing profit.

As a result of inefficient pricing strategies, gift retailers very often lose revenue and hope for growth. Retailers need to revamp their pricing strategies to remain competitive.

Is AI a recipe for success when it comes to pricing?

To be able to come up with data-driven pricing decisions for the whole product portfolio in real-time, retail teams require significant computational power. That’s where AI jumps in.

A dense neural network behind the algorithm used in AI-powered price recommendations systems considers the infinite number of pricing and non-pricing parameters such as price elasticity, website traffic, seasonality, competitors’ prices, and price elasticity when setting prices. It is quick, learns as it goes, and comes up with 100% data-driven price suggestions for the whole assortment which altogether maximises sales of the whole portfolio.

How a UK-based retailer used AI to boost revenue and sales

The UK gift retailer Find Me a Gift used to cut prices for a range of items blindly to attract more customers during holidays. For a company making 50% of its annual turnover in the run-up to Christmas, slashing prices would seem a reasonable move.

But eventually, this would not translate into growing revenue as the retailer would not factor in all the necessary parameters like price elasticity or seasonality when setting prices. “We were running around selling lots of stuff, but we wanted to find a way to make each pound work harder for us,” commented Jean Grant, purchasing and product development senior manager for the company.

Find Me a Gift wanted a more effective solution to increase item sales and revenue. The retailer partnered with Competera, a retail price optimisation company, to test the efficiency of machine learning in optimising pricing. During a five-week market test, Find Me a Gift applied regular and promo price recommendations for some 600 SKUs generated by the self-learning algorithm.

 

The market test resulted in Find Me a Gift not only boosting its item sales by 24.7% but also increasing revenue by 9.3% for the selected products vs the rest of the retailer’s product range. Such an outcome can be attributed to the ability of the algorithm to take into account thousands of latent relationships inside a product portfolio and recommend individual prices for every product, which altogether maximises sales and revenue of the total portfolio.

 

Today Find Me a Gift keeps on “delivering happiness around the world with its memorable gifts and experiences,” as Adam Gore, the retailer’s founder and CEO, stated in an interview.

 

All in all, retailers need to rethink many things when it comes to the very core of their businesses, including such an important component as pricing. Many companies remain paralysed by the changes in the market, while others demonstrate readiness to adjust to the changing reality and milk the most of the emerging opportunities. Such forward thinkers are already embracing AI in many areas, including pricing, and grow significantly.

Vladimir Kuchkanov is a pricing solutions architect at Competera

 

Image: Fotolia

Linked InTwitterFacebookeCard
Add New Comment
You must be logged in to comment.

The InternetRetailing Newsletter

A curated update containing news analysis, reports, podcasts and opinion - completely free and delivered three times weekly

Become a Member

Create your own public-facing profile
Gain access to all Top500 research
Personalise your experience on IR.net
Internet Retailing
We are the magazine, portal and research source for European ecommerce and multichannel retail, hosting the board-level conversation for retailers, pureplays and brands across all of our platforms. Join the conversation.

© InternetRetailing Media

Latest Tweet

Internet Retailing
Tamebay
eDelivery
Twitter
Facebook
Linked In
Youtube
RSS
RSS
Youtube
Google
Linked In
Facebook
Twitter