Dynamic Pricing and Personalization With AI
Technology is changing the way retailers make several business decisions, from shop layouts and merchandising to customer experience. Retailers are making use of Big Data and other tools like AI and machine learning to provide personalized services to customers. This includes product pricing.
Big data and data analytics have enabled dynamic pricing for sellers, both online and offline. Your pricing strategy can be deemed dynamic if it takes into account market trends, competitor pricing, customer behaviour, and more factors to set the optimum price for your products on a regular basis.
AI and machine learning have enabled dynamic pricing tools to analyze various factors, take in your own business constraints, the expectations of your customer base, the need of individual customers at a particular time etc to dynamically change the prices and optimize them, without manual intervention.
Dynamic Pricing as a Part of Personalization
More and more customers are expecting a personalized experience as they shop. They want the shops they often visit to take into account their buying patterns and preferences and expect product suggestions and promotions to be targeted, to match their needs.
Personalization begins with recognizing and greeting the customer, to suggesting appropriate products or special offers, to meeting customer expectations in prices and service.
From Data To Decisions – What Does Dynamic Pricing Involve?
If you want to implement dynamic pricing for your products you require a lot of data. Price monitoring tools in your retail management software can gather data about competitor pricing for various products, their stocking levels, data about current market trends in prices, about customer behaviour, etc.
All this data is then analyzed to gain insights into key factors for price changes. AI and machine learning can then be used to learn from how past price changes affected sales, and arrive at the optimal price for each product at the current time. This cycle of gathering data, analyzing data, and making intelligent decisions on price changes is an ongoing process, resulting in dynamic prices for your products- prices that vary at different points in time depending on the data crunched at that point.
Some Dynamic Pricing Scenarios
The foremost idea of dynamic pricing is to allow a business to respond to changes in the market, quickly. For instance, if a major competitor is out of stock for a particular product you may be able to increase the price for that product because customers who need that product now have fewer sources to buy it from.
For online retailers, dynamic pricing becomes all the more important. There is a lot of scope to monitor customer behavior for pricing decisions and personalization. For instance, if a customer adds a product to their wish list and keeps coming back to it often, then the customer is very interested in buying it.
- If the customer decides to add the item to their shopping cart, you may decide not to offer any special discount because he wants the product and has added it to the cart at its current price
- If, on the other hand, the customer keeps visiting the product page but puts off the buying decision, you can send a special discount notification to his phone, a time-limited offer that creates an urgency, motivating the customer to buy it now to take advantage of the special price
- For the first scenario, you can also offer a discount at checkout, a pleasant surprise to the customer. This way, you may also succeed in making him a repeat buyer, a loyal customer who trusts you.
Amazon is the leading example of a retail business that makes the best use of dynamic pricing. They constantly monitor competitor prices, customer behaviour, the prices set by third-party sellers on their own site and other factors to determine the best prices for products that they sell directly. Amazon prices for various products can thus change frequently, to ensure that they always offer the best price.
Benefits of Dynamic Pricing
Maximized Profits: Dynamic pricing empowers businesses to set the optimal price point at any given time, ensuring maximum profitability.
Competitive Edge: By monitoring market trends, businesses can adjust their prices to remain competitive and capture a larger market share.
Inventory Management: When combined with inventory data, dynamic pricing helps prevent overstocking or understocking, thus minimizing losses.
Personalization: Tailoring prices to individual customer behavior fosters a personalized shopping experience, enhancing customer loyalty.
Downsides of Dynamic Pricing
- Perceived Unfairness: Constantly changing prices might lead to customers feeling unfairly treated if they see others getting a better deal.
- Complex Implementation: Setting up dynamic pricing systems can be technologically challenging and might require initial investment.
- Lack of Transparency: Not providing clear reasons for price fluctuations can confuse customers and erode trust.
Is Dynamic Pricing Fair?
The question of fairness often arises when discussing dynamic pricing. While it’s true that some customers might benefit from lower prices due to the flexibility of this strategy, dynamic pricing is inherently neutral. It’s more akin to the fluctuating prices in the stock market, adjusting based on real-time demand and supply.
Types of Dynamic Pricing
- Time-Based Pricing: Prices vary based on the time of day, week, or season. This is common in the airline and hospitality industries.
- Demand-Based Pricing: Prices rise during peak demand and decrease during off-peak times, as seen in ride-sharing services.
- Segmented Pricing: Different customer segments see different prices, catering to their willingness to pay.
- Penetration Pricing: Lowering prices initially to enter a new market, with the intent to increase them over time.
Customer Perception of Dynamic Pricing
Dynamic pricing is a good strategy from the point of view of retailers, both retail and e-tail. However, a recent survey revealed that a majority of customers do not like the constant price changes caused by dynamic pricing.
However, when that research data is broken down into age groups, it was found that a larger number of young customers welcomed dynamic pricing. They saw this as a way to get the items they needed at the best prices possible. This was because customers who were more savvy with technology were aware of price comparison websites that would help them find the best price for a particular product online.
New Factors in Dynamic Pricing
As more customers make use of virtual assistants like Google Home or Amazon Echo & Alexa to shop, merchants can begin to gain new insights into customer behavior, Questions customers ask the virtual assistants can provide a view into the factors that influence their buying decisions. The dynamic pricing software can then use this information to make pricing offers to the customer.
The Future of Dynamic Pricing
Though some studies show that customers do not appreciate constant price changes, dynamic pricing combined with AI is a good strategy for retailers. Not many retailers would change their prices as frequently as Amazon does. Amazon can afford to do this because they generate huge volumes of sales and their customers come to them expecting the best prices.
For other retailers, dynamic pricing on a less frequent basis would work well. This works not just for ecommerce, but for in-store sales too. Sales persons can have apps installed on their mobile phones that link to the dynamic pricing app. This app can advise them on the best prices to offer on a product to a customer they are interacting with, show related products to promote and so on.
Dynamic pricing is an essential need in retail business and is here to stay. Artificial Intelligence can make dynamic pricing more relevant, the informed decisions can make the prices more acceptable to customers, as a part of personalized service.
You can personalize your pricing for your customers, be agile in responding to market changes, and increase revenues, using a Dynamic Pricing solution.