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Dynamic Pricing & Promotions in a Digitally Empowered World

Fri, Jul 10, 2015

Dynamic Pricing in the Digital Economy

In the digitally enabled world of today, advancing and improving a best-suited pricing and promotional strategy is a complex riddle – it’s certainly hard to achieve, but rewarding for those who fill the bill.  By using a customer intelligence engine that relies on predictive analytics to understand purchasing behavior, fashion retailers are able to give customers what they exactly need – dynamic pricing and compelling promotions.

The Jackpot: Increased sales and revenue margins. Identifying which pricing strategy, when and why, helps fashion retailers develop relevant promotions, get closer to the customer, and increases their chances of having a trail of loyal followers, in the long-run. 

The Digitally Enabled Consumer

Today’s tech-savvy customers compare prices in-store, online and on the go. With a constant look-out for the best deal, digitally enabled consumers are price aware, price sensitive and heavy price influencers. To soar in this challenging environment, brands should trump on this ability to dynamically compare their prices across all channels, in real time.

The Customer is King Sense__Respond_-_Image_1

With a dynamic, personalized pricing strategy follows convenience for omnichannel customers using different channels, and expecting a delightful shopping experience.

Consider Denise, who wants to buy an elegant pair of silver pumps that suits a number of grand occasions. She is looking for a durable, high quality pair at an affordable price. While she does her research online, reads reviews on social media and compares prices, a particular retailer provides Denise with a 30% discount on a pair of shoes that caught her eye and another 20% if she registers as a member. Today must be her lucky day. A 50% discount! Denise loves the offer. Before going ahead and making the purchase, she decides to visit the retail store to try on the pair of pumps. When she gets to the store, she is happy to see that the online and in-store prices and discounts are identical. She registers as a member and purchases the pair of pumps she located on-online.

In the face of such diverse options, how would a fashion brand decide on their pricing strategy?

As opposed to simply “tacking on” an extension to a POS system, retailers that leverage a robust foundation that digitally enables associates to gather and receive information and browse available products will empower those associates to build a more personal relationship with their customers, resulting in increased brand loyalty.

Taking a Step Further with Personalized Pricing Sense__Respond_-_Image_2

After her initial purchase of silver pumps, and a few consecutive purchases thereafter, Denise was identified as an ‘Elite member’ (loyal shoppers who made more than 10 purchases over the past year) of the brand. By identifying Denise’s preferences via social media websites, frequency of in-store visits, wish-list (on-line and in-store) and past purchase history, the retailer uses a pull-based strategy and extracts data from these channels in order to provide unique pricing and promotions to their segmented Elite members. 

How Does this Work?

Personalized pricing using a Pull Promotional Strategy: Extracting data from social media feeds will help the retailer gauge Denise’s lifestyle, her likes and dislikes & create a basic foundation for her profile. (Age, Birthday, Workplace, Interests, Marital Status) In addition, by extracting transactional data from purchases she’s made in-store & on-line, and identifying the frequency of trips she’s made to the store on a monthly basis, a personalized price can be generated. This price may vary for each customer. Since Denise has been identified as a loyal customer, she has a higher probability of receiving a better price in comparison to another customer. 

Predictive Promotions: Unstructured data gathered via Denise’s spending patterns and past purchase history will showcase the number of items purchased within a chosen period of time. In Denise’s case, a consistent amount of 6 items are purchased in a month. As she has been identified as an elite member, the retailer presents a 40% discount on all items on Denise’s wish-list. This is a predictive promotion. The retailer knows that a minimum sale of 6 items is made, each month. By giving away this discount, Denise is more likely to buy additional purchases during this particular month. In addition, the retailer gives out free shipping for all products Denise purchases online. 

Using a behavioral-based predictive analytics platform, such as the Customer intelligence Engine, comprising of the Customer Journey, Social Data, Past Purchase History and Inventory Availability paves the way for a dynamic, personalized pricing strategy. This would lead to an increase in the customer lifetime value, boom customer conversion & retention rates, which in turn would increase revenue. 

Value Your Customers

Fashion retailers that offer personalized and dynamic pricing, at scale, have a competitive advantage in the market. By tying together the potential of big data and predictive analytics, retailers are able to determine the price that meets customer expectations and deliver promotions whenever, wherever. Retailers must realize that this is an essential capability for steering their business in a positive direction and achieving exceptional growth.