As 2018 approaches, the retail ecommerce industry is seeing a significant shift towards increased personalization. In fact, 79% of organizations that exceeded their revenue goals had clearly documented personalization strategies. The reason for this success is that businesses are beginning to recognize and address the fact that each consumer is an individual—with individual needs, wants and likes. And, one way ecommerce retailers are tending to this reality is by personalizing the existing practice of dynamic pricing.
Dynamic pricing has helped business owners determine the timing, placement, and product price points that work best to engage a website visitor to purchase a good or service.
Personalized dynamic pricing offers personalized incentives and pricing based on each individual consumer and their behavior, such as previous purchases or loyalty to the brand.
Both methods are sophisticated in that they are powered by varying degrees of artificial intelligence (AI), which is used to analyze and provide insights on large amounts of consumer data. However, there are key differences that are causing dynamic pricing to decrease in popularity while personalized dynamic pricing begins to soar in effectiveness.
Rather than present only one price at all times, a website that presents dynamic pricing options may offer different prices in a given time period. This can be based on generic factors such as seasonality, time of day, or supply and demand.
RetailWire explains that while the price may fluctuate in a dynamic pricing model, “…everyone will see that [exact same] price no matter who they are, so long as they are on the product detail page at the same time.”
For example, this item on sale through Amazon has had various price fluctuations experienced in a 30 day period. The price was adjusted back-and-forth roughly between $85 and $100 during the month.
What’s lacking in this dynamic pricing example is that any consumer who wished to purchase this item would have seen the same price, on the same day, at the same time as all other potential shoppers, regardless of the inherent differences between them. This is where dynamic pricing and personalized dynamic pricing differ (and where things start to get interesting).
Personalized Dynamic Pricing
Personalized dynamic pricing empowers ecommerce retailers with the ability to target unique consumers with unique price points. AI provides data that helps business leaders target exactly what price will work, at what place and time, to increase the likelihood that a given consumer will purchase.
In contrast to dynamic pricing, personalized dynamic pricing takes into account a number of unique factors for each consumer, such as:
- Shopping and browsing history
- Hobbies and interests
- Brand loyalty
- Special events such as holidays, birthdays, or anniversaries
- Supply, demand, and competitive pricing
While dynamic pricing changes according to more generic variables, personalized dynamic pricing is specifically consumer-focused, reflecting a unique offer per individual shopper.
The image below shows an example of what personalized dynamic pricing might look like for individual buyers of the same airline flight.
Source: Harvard Business Review “How Retailers Use Personalized Prices to to Test What You’re Willing to Spend” KLAUS MEINHARDT/GETTY IMAGES
These airline plane seats are each in coach class and in essence the same. However, the prices paid vary drastically because they were based on the unique behavior of each individual consumer. Perhaps, for example, frequent flyers receive loyalty incentives while first time travelers on this airline or to the given destination receive a discount.
There are seemingly endless opportunities for a company to offer personalized pricing based on a variety of demographics — location, purchase history, competitor price matching. Consumers increasingly desire special treatment, and that’s where personalized dynamic pricing delivers.
Key Takeaways: The Future is Personalized Dynamic Pricing
It is clear that personalized dynamic pricing will continue to lead the way because it takes into account the unique needs of each consumer. Not only is this method beneficial to ecommerce executives, it is highly valuable to consumers as well.
A recent study by Virtual Incentives discovered that 56% of consumers surveyed said that receiving a personalized incentive would improve their consideration of the respective brand. These consumers agree that personalization makes brands seem smart, unique, and caring.
As for what will happen to dynamic (or traditional) pricing models, the numbers don’t lie. More digital marketers view personalized dynamic pricing as an opportunity—up from 31% in 2016 to 33% in 2017. Meanwhile, interest in dynamic pricing has waned from 28% in 2016 to 22% in 2017.
What’s more, fixed pricing models are becoming more and more obsolete as AI algorithms efficiently (and affordably) continue to progress the changing landscape of both digital and in-store payment structures.
Personalized dynamic pricing optimizes price points with the aim of increasing buyer interest and likeliness to purchase. Brands wishing to remain competitive will have a difficult time not adopting a technology that offers so much opportunity. Therefore, ecommerce companies wishing to stay ahead of the competitive curve will need to adopt AI to assist in crafting the unique pricing opportunities afforded through personalized dynamic pricing.