How to Solve the Geo-Pricing Problem

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How to Solve the Geo-Pricing Problem

By Julien Gautier, ActiveViam - 07/16/2019

As the retailing space becomes more and more competitive, traditional retailers — from Kohl’s to Bed Bath and Beyond — are all taking a long hard look at their pricing operations and strategies. But with Amazon literally capable of adjusting pricing on inventory every 10 minutes, the focus for retailers has once again shifted to their geo-based pricing capabilities, and if they are doing enough to help them remain competitive.

Retailers almost universally understand the importance of tailoring their pricing based on specific regions — taking in competitive, demographic, purchasing and other related data to better tailor pricing to specific customers.

However, although traditional retailers realize how imperative geo-pricing is, they do not always have the adequate infrastructure to drill down to the granular level that they need to. Moreover, apparel retail is home to many pricing challenges that are uncommon in other retail verticals.

With that in mind, below are the three challenges apparel retailers need to focus  on to further optimize their geo-pricing.

Identifying key competition metrics

In many retail categories — such as consumer electronics or grocery — keeping tabs on competitor pricing is relatively easy given that retailers can easily compare their own price on a specific product to what the price of the same product is at another retailer’s location. However, in apparel, with so many varieties of goods on offer — not to mention sizes and colors — and many of them exclusive to the designer, it is difficult to make an “apples to apples” comparison on price between retailers. Therefore, apparel retailers are forced to generate broader competitor pricing brackets based on factors such as style and brand. Unfortunately, many retailers do not have the technology in place to help them make these general pricing brackets as nuanced and specific as they need to be.

Lining up local prices with KPIs

Retailers have become pretty comfortable and effective at building and applying algorithms to calculate local prices. However, one of the key challenges they continue to grapple with is how these prices and price adjustments “project out” and impact KPIs. For example, simply setting and tweaking a price to make it as competitive as possible may seem to be the right decision on the surface, but if it undermines KPI performance this can have a very detrimental impact on revenue health. This is why retailers need to be able to connect the dots and make sure that each geo-price and its associated adjustments serve its overarching goals.

Getting granular

Today, many if not all retailers have some sort of categorical approach to pricing — whether it be a geographic-based approach or one based on other factors such as store size or demographics. However, given the surge of competition and continued consolidation in the retail space, price optimization needs to become even more specific, allowing retailers to adapt pricing from store to store. Unfortunately, many retailers lack the necessary tools to be able to accomplish this. Therefore, retailers need to find ways to modernize their pricing technology infrastructure so that it can take in each location’s competition, inventory levels and other related information to optimize each specific shop based on its own unique circumstances and data.

That said, this can become particularly challenging for apparel retailers when markdowns need to occur. Markdowns are determined by a complex web of factors, so coordinating and optimizing markdowns across different locations so that as little margin as possible is sacrificed can be painstaking. This underlines the need to modernize pricing operations as much as possible.

Speed of pricing adjustments

While having the right tools in place to pull in the necessary data is very important, it is only part of the battle. Once the proper technology instruments are being leveraged, retailers now need to be able to harness the immense amount of data they are receiving so that they can begin to act on the insights they are gleaning. Doing this in apparel retail can be incredibly challenging given the speed at which data is flooding in, and how often new products are introduced and old ones are phased out. As such, retailers also must have the proper analysis and BI structures at their disposal so that they can optimize prices as quickly and as accurately as they need to.

Getting localized pricing in retail right is hard enough to begin with, but with so many idiosyncrasies, apparel retail is one of the most challenging. However, by taking a more technologically advanced approach, apparel retailers can not only achieve better internal results, but also can beat out local competitors around each and every one of their shops.

Julien Gautier is Director of Marketing at ActiveViam.