Dynamic pricing is a strategy that all online retailers must pay attention to. It is a supply-and-demand-based pricing model than enables real-time price changes in order to make the most out of high demand, clear out stock when needed, or preserve stock when running low. To put it simply: dynamic pricing helps boost profit margins, revenue, and can complement any existing pricing model (offering significant benefits).
Dynamic pricing has changed during the four decades it has been around, largely thanks to the emphasis Amazon and other marketplaces have put on it. The trends that have emerged around this pricing strategy are worth exploring for established data-driven practitioners and newcomers alike that want to boost profit and revenue over time.
Pricing in online retail can be a complicated endeavor without the help of pricing algorithms.
Modern Dynamic Pricing Trends Retail Needs to Know
1. Competition is Only Getting Stronger
Few retailers exist on an island without competition. This means that direct-to-consumer upstarts are coming to disrupt industries and behemoths like Amazon are adding product categories each day. As a result, retailers need to stay on their toes and understand when a new competitor has entered the market and how their pricing compares. Based on this information, the next step is to take appropriate actions, like repricing, to maintain a robust customer base.
Implementing dynamic pricing has never been more important than it is right now because more shoppers are choosing to buy online than ever before. Presenting prices that make sense within the competitive landscape is a requirement for surviving and thriving in online retail. When the competition is running out of items that are in high demand, your pricing model needs to be ready to answer to this with real-time pricing changes when it counts most. Quick actions in cases like these will have a massive impact on profit margins.
2. Consolidation Saves Time and Costs
Dynamic pricing requires countless lines of data in order to make an effective pricing decision using an algorithm. One of the most important types of data required to arrive at an optimal price is price intelligence. Opting to use different vendors for repricing and data is a cumbersome undertaking that can not only be confusing to keep track of but potentially lead to pricing errors. Instead, offering the best prices requires choosing providers that marry data and repricing capabilities. This consolidation makes price optimization easier, potentially more accurate, and less costly because the entire process is under one roof.
3. A Complete View of Relevant Data is Required
Many established retailers tried other pricing strategies before they landed on dynamic pricing. This means that they potentially have decades of sales data lying around from those other pricing endeavors. While it is nice to include competitive pricing intelligence and SKU prices, a data-driven algorithm benefits from the most complete set of data. And, for omnichannel and brick-and-mortar leaders, connecting that point of sale data could be especially helpful as well. Feeding all these types of historical data into dynamic pricing algorithms gives added context to help determine the most effective price recommendations.
4. Price Elasticity Meets Time-Based Pricing
Dynamic pricing has historically provided a deep understanding of pricing’s relationship with buying patterns and enables price changes that simply make sense. This still holds true today: dynamic prices can change throughout the day, but only to a certain extent. Shoppers don’t want to see prices changing wildly from one hour to the next. This can negatively impact trust unless you approach it the right way.
Some customers might use Honey, the Chrome extension that aggregates online coupons and shows pricing history on product pages. Put stopgaps in place to make sure that your prices aren’t extreme because this could send signals to shoppers that they should simply wait until the price swings back to the lower end of the spectrum before they choose to buy. In order to avoid this, first test the price elasticity of products in order to determine the minimum and maximum. Once you have that data, you can match it up against the competition’s prices and market forces to only reprice within boundaries that protect both profit margins and customer trust.
5. Dynamic Pricing Needs a Healthy Dose of Human Intelligence
A dynamic pricing strategy is the most effective way for retailers to stay current and always put their best foot forward (without resorting to manual and time-consuming practices). It is a seamless process that connects disparate data and makes sense of it all. But retailers still need to keep an eye on their key metrics to see if any modifications are needed.
Say you secure a new supplier for an item that is in high demand, but has been higher cost that a competitor’s offering. It is possible that you will be able to reduce the price on that SKU over time. That new information should be input into the dynamic pricing system to make sure that the price minimum and maximum are accurate. Alternatively, if a certain competitor has started to violate minimum advertised price policies across the board, it might be wise to take them out of consideration.
Retail leaders never want to reprice based on skewed or out of date insights, so instead stay focused on the competition that operates within the established rules of online selling. Strong dynamic pricing models have smart analysts behind them to augment automatic data with human intelligence that covers trends and updates that arise.
Pricing in online retail can be a complicated endeavor without the help of pricing algorithms. There are so many types of data to keep track of from historical sales to web traffic to competitive pricing trends. In order to make the most of this pricing opportunity, eCommerce leaders need a partner to wrangle all the data and deliver optimized prices in real-time that will put customer demand at the center.
Wiser Solutions enables complex and automated pricing strategies that take into account all relevant data and prioritize profit and revenue optimization. Learn more about dynamic pricing here.