A lot has been changing and growing in technology, therefore, dynamic pricing strategies are only becoming more reliable and useful. Indeed, even a giant retail bank that uses pricing algorithms can offer deposit rates based on the checking account activities of their clients. In order to do so, it identifies deposit flows that occur between the bank and then another savings bank, consider what that client’s relationship is with that bank, as well as forecast both the revenues and the rate of the rivaling bank that way they can make the best rate possible. Through these kinds of promotional offers, banks can get a much greater response out of their promotions.
At the same time, revolutionary services such as Uber and the online retailer Amazon, are gathering and taking advantage of various other kinds of data sources so that they can enhance how effective their pricing algorithms are in order to make the highest revenue possible. Based on a case study about Uber drivers, the algorithms of the firm take advantage of how sensitive drivers are to different kinds of nudges such as heat maps, messages, and incentives that way they can impact as well as boost the supply at the height of demand periods.
Based on Amazon’s Privacy notice page, they gather and evaluate whatever they can including purchase histories, the items viewed, the items that had been looked up, reviews, wish lists, as well as the amount of time spent on specific pages. With the help of all of that information on how customers shop, Amazon has a better understanding of what their customers want, the things that the like to buy, as well as at what prices they will actually make purchases.
In addition, the heads of companies are starting to realize that a dynamic pricing strategy that utilizes both big data and artificial intelligence is able to assist them in getting a competitive advantage over their competitors. That being said, though, whenever a firm goes into a new dynamic pricing market, there are a few things that they can take advantage of in order to make sure that they succeed.
Humans and Machines
You definitely will have come across pricing decisions that had been made by advanced methodologies and algorithms despite the fact that there was a chance of them not being entirely incorporated through the decision makers as well as the sales team. This often occurs whenever staff aren’t completely on the same page with the analytical pricing strategy. For instance, at Simon-Kucher & Partners, they had been working with a popular American department store that had recently taken advantage of markdown pricing algorithms that way they could deal with the markdowns of their styles that weren’t selling as well on a much better level. That being said, though, their human staff did not comply completely with those pricing recommendations which the pricing algorithms had come up with. Even though the algorithms had caused revenues to increase, if the staff had actually complied completely, they could have seen their revenue increase a whole lot more. Therefore, it is important to ensure that frontline sales employees are completely aware of the process from the very start of incorporating an advanced analytical algorithm into the company.
Don’t Only Consider Buying, Build It!
When it comes to those who provide pricing analytics solutions, there aren’t that many good ones to choose from. For one, there are startups that are either completely new in the market or very well-known companies and consultancies. That being said, we have to understand that they “revolutionary” pricing capabilities that had been developed by Uber and Amazon, can’t be utilized with success all that often if you simply copy and paste an algorithm that had been developed at some other firm. Instead, those firms had created their own capabilities towards pricing strategies and analytics within their firms. Therefore, if you completely want to take advantage of both AI and pricing analytics, you have to make your own algorithms, regardless of whether you outsource the execution to a provider.
Novices Go Into it Fast
When you are just getting into dynamic pricing, it may be difficult at first to utilize a top-of-the-line AI-powered pricing algorithm that has numerous predictive factors as well as situational information. However, the best artificial intelligence for pricing first needs a company that has a good pricing strategy that way their pricing model goes hand in hand with their growth strategy. Therefore, if you would like to boost their cross-selling rates or if you would like to decrease the customer churn rate, you want to first start by figuring out if you have the best pricing strategy based on subscription, bundling, or freemium, in order to reach it. These machine learning algorithms also have to work nicely with the workflow of the company along with their current sales processes. In the case that a business is selling through digital channels, for instance, the information that impacts the way customers behave should not be looked at as invasive.
Suppose that you are working through a sales force, you want to make sure that your algorithms go hand in hand with how you and your customer interact. Indeed, with the help of those first base steps, you will be able to make the best environment for choosing the machine learning method and data requirements that would be the best for you. As soon as you have incorporated the machine learning method into it, you also want to make sure that you constantly working on improving the algorithms, too.
Make sure Your Data is Accurate
Data is crucial when it comes to machine learning algorithms. If you don’t have all of the data or some of it is inaccurate, you won’t do nearly as well as you could with those machine learning algorithms. You could think about utilizing a third-party supplier when it comes to data collection, but it is not recommended that you depend entirely on outside sources for information. Indeed, the best thing that you can do is take advantage of your own customer databases as well as data sources, as those are the two things that will give you the best competitive advantage possible.
Analytics that is backed by AI can provide firms with the chance to beat out their rivals. That being said, AI-powered pricing that you can depend on needs a solid pricing strategy that way you can make sure that the pricing suggestions go hand in hand with the expansion strategy of a firm, the data science capabilities to make sure that both the predictive algorithms and machine learning is accurate, as well as the technical structure for the trial-and-error method so that their algorithms are able to react quickly to any changes that may occur.