September 27, 2022 By: Protik Kundu
Gross Merchandise Value (GMV) represents the overall value of goods sold on a platform during a specific time period, such as on a quarterly or yearly basis. Whether a retailer chooses to sell on the marketplace or operate its own online store, GMV is a crucial business performance metric for any retailer focused on growth and profitability.
What is Price Optimization and Recommendation Solution?
According to a KPMG report, 65% of consumers look at the price information of a product while in a shop and a Mckinsey report indicates that 30% of consumers consider price as one of the key drivers to switching brands.
In fact, with the rise in e-commerce sales, and the frictionless comparison enabled through digital commerce, competition in the market has gotten much more aggressive and real-time. Businesses need to keep an eye on their competitor’s pricing strategy while setting prices to get the much-needed competitive edge in the market i.e., augment their demand-driven/ inside-out pricing strategy with a market-driven/ outside-in pricing strategy.
Price Optimization and Recommendation Solution enables retailers to provide truly optimized pricing to their customers and prospects leveraging both demand-driven & market-driven pricing which positively impacts their GMV as:
- Customers are more satisfied as they always get the best deal available at any point of time, which increases brand loyalty, repeat business, and increased market share.
- Retailers increase their profitability through timely mark-ups and markdowns & reduced effort in pricing decisions.
Price Optimization and Recommendation Solution Components
The price optimization and recommendation solution have five key modules that can be selected and customized to specific retailer needs:
- KVI Module: The key-value-item (KVI) module dynamically assesses user behaviors like click rates, search data, and product reviews to determine how much each product influences consumer pricing perception.
- Competitive Response Module: The competitive response module suggests price modifications based on real-time competitive pricing information.
- Long Tail Module: Through sophisticated product matching, the long tail module assists a retailer in determining the introduction pricing for fresh, refined, or long-tail goods.
- Elasticity Module: The elasticity module accounts for a wide range of variables, such as periodicity, cannibalization, and competitive maneuvers, in order to determine how the price of a product impacts demand.
- Omnichannel Module: The retailer’s online and offline channels have their pricing synchronized through the omnichannel module.
Approach Towards Implementing Price Optimization and Recommendation Solution
There are three main phases in implementing the solution:
Step 1 – Identify Competitors & Rank Them
Depending on the business’s preferred sales channels—online, in-person, or both—competition may differ. While a retailer can sell items through several channels, the competition may only be using one channel or the other way around. The next step will be to get the data on how frequently prices change across each channel for each product and its competition, including substitute(s). However, not all competitions are created equal so it’s better to do competition ranking based on market impact and importance across the sales channels.
Step 2 – Gather Competitive Pricing Data
Pricing intelligence is now a lot more practical and scalable because of automation. While manual data gathering is always an option, as is developing an internal solution, retailers should implement a robust and automated framework to get competitive pricing information. An automated system will therefore match that product details across competing websites and online platforms, reporting on the pricing displayed for each product.
Step 3 – Analyze, Optimize and Recommend
Price optimization and recommendation solutions highlight the pricing strategies of competitors at scale. It allows a retailer to identify how often and why the prices are changed. This provides insight into setting up the ‘right’/ recommended price for a specific product in the business. The dynamic knowledge of competitive price markets aids in extrapolating data to influence internal pricing strategies to increase GMV.
How Price Optimization and Recommendation Solution Increases GMV for Retail Businesses
Below are a few ways how the retail industry can leverage Price Optimization and recommendation solution to achieve higher GMV:
- Increase Market Share & Conversion Rate: Retailers can use the insights from the Price Optimization and Recommendation solution to improve in their pricing strategy and beat the competition. For example, retailers can make their products the same price as the competition while offering more features and directing the customer to a direct product comparison platform. Customers will likely purchase the more feature-rich products within the same price range, so the business will gain market share. The Price Optimization and Recommendation solution increase customers’ confidence and trust in the price of the product & services.
- Improves Profitability of Retailers: The solution prevents unnecessary markdowns and reduces the effort of the pricing team with automated dynamic & smart pricing strategies- Hyperautomaton of Pricing is how Price Optimization and Recommendation Solution will pave the way to increased GMV.
Customers frequently compare pricing these days before making purchases of goods or services. Retailers need to implement a dynamic pricing strategy that includes external data like competitive prices along with the internal cost & demand data for better ROIs and increased GMVs.
For retail and CPG industries, JK Tech has established a reputation for full-service hyperautomation services. Our extensive experience in operationalizing automation will ensure that you have an appropriate hyperautomation strategy and solution that will significantly improve your competitive advantage with an efficient and effective end-to-end business process.
