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Are you ready to harness the power of data-driven decision-making? Join Express Analytics at eTail West 2025, where retail and eCommerce leaders come together to shape the future of the industry!

📅 When: February 24-27, 2025 📍 Where: JW Marriott, Palm Springs, CA

At Express Analytics, we help businesses turn raw data into valuable insights. Stop by our booth to discover how our advanced solutions in customer analytics, RFM modeling, lookalike marketing, and supply chain optimization can revolutionize your retail strategy.

Why Visit Our Booth?

✅ Live Demos – Experience our analytics tools in action and see how they drive smarter decisions. ✅ Expert Consultations – Connect with our team of data scientists and industry specialists. ✅ Exclusive Insights – Learn how AI-powered predictive analytics can enhance customer retention and maximize ROI.

Don’t miss this chance to explore innovative solutions, network with top experts, and take your business to the next level.

Recommendation systems are also called data filtering tools, and they use machine learning algorithms and data analysis concepts to recommend the relevant product to the user.

The main objective of any recommendation engine is to encourage demand and engage users.

What is the biggest threat to retail today? Why are traditional retail businesses witnessing a steep downfall in their top and bottom lines? Forget about the numbers, why is the very presence of real-world retail suddenly endangered? Dynamic pricing is the inevitable future of traditional retail.

This may surprise you, but the answer is not the COVID-19 pandemic. It is retail’s overarching archenemy, e-commerce. In this blog post though, we shall explain how traditional retail can overcome the challenge posed by e-commerce, turning one of its most powerful weapons against it – that of dynamic pricing.

What Is Dynamic Pricing?

Dynamic pricing tools take into account a combination of historical and real-time market data to offer price suggestions. The data can range from past performance to geography to seasons or even local events. The algorithm makes frequent changes to rates based on such data inputs, thus helping companies stay competitive at all times. Such pricing can be based on a group of people or on the passage of time.

Dynamic pricing is most suited for highly competitive industries which enjoy elastic demand for their offerings. Airlines, hospitality, events, transportation, and most recently e-commerce have successfully implemented dynamic pricing. The latter has always been around, but the underlying technology for its implementation is what has changed and evolved over time.

So Why Should Traditional Retail Also Deploy Dynamic Pricing?

This is a very important question because tackling e-commerce is merely scratching the surface. Traditional retail has always operated on fixed pricing. Fixed pricing means that there is no flexibility for the retailers to attract more customers and build brand loyalty. Simply lowering product prices is also detrimental to their business eventually, since it brings a roundabout change in customer’s overall expectations. Also, fixed pricing holds businesses back on all the potential incremental profits that can be earned if dynamic pricing is implemented to take advantage of the shifts in customer loyalties, demand and supply, and the broader external environment. It also allows businesses to carry out a huge number of transactions without having to worry about reduced margins.

Various studies show that dynamic pricing has proven itself to grow in revenue by up to 30% and increase profit margins by about 11%. These numbers cannot be ignored by retailers fighting for every cent and dollar. The potential to grow is seemingly limitless. Here’s what a Forbes report had to say about the future of dynamic pricing:

“In the not-so-distant future, virtually nothing will have a fixed price. Say goodbye to the familiar $1.99 and hello to a price between, say, $1.39 and $2.17, based on changing supply and demand. This is the phenomenon of dynamic pricing, and it is already rapidly changing the way we buy goods and services and dramatically reshaping our economy”

“Companies are using artificial intelligence (AI), machine learning (ML), and automation to balance demand with supply in near real-time. For the first time, all the economic forces at work (the “hand”) are finally visible in the data. As a result, for the first time ever, businesses no longer have to use guesswork to set their prices: They can use data to understand what their prices should be and automatically change as supply and demand fluctuate.”

Dynamic pricing can help retailers to reduce waste by enabling them to sell “unsellable” products. For instance, electronic products being replaced by newer models, or grocery and consumer perishables nearing their expiration. Retail outlets discard such perishables worth thousands of dollars daily. Giving customers incentives by way of reduced prices to purchase such items will significantly increase their salvage value to the retailers. AI-based dynamic pricing engines can correctly identify the exact price needed to move products, protecting sales and profit margins.

Another major advantage of dynamic pricing is its ability to establish strong brand loyalty. For example, if a dynamic pricing model is effectively incorporated into a firm’s CDP (customer data platform), its AI, ML, and predictive modeling capabilities can provide retailers the opportunity to generate attractive and compelling offers for their customers. The dynamic pricing engine can be used to generate user-specific offers in the form of discounts, coupons & vouchers, and bundles for exactly those products on which the customers are most likely to spend on. It makes a very solid use case for retargeting customers who can be encouraged to revisit the stores and make follow-up purchases.

Now that we have covered the what and the why, it is time for the how.

How Can Retailers Implement Dynamic Pricing?

The first thing you need to know is that dynamic pricing does not require some over-the-top, fancy or complex software. Here’s what a McKinsey report says about it:

“Dynamic pricing isn’t just for travel companies or e-commerce giants, and it doesn’t necessarily require ultra-sophisticated software that changes every product’s price multiple times a day. Even traditional retailers can reap tremendous benefits from merchant-informed, data-driven algorithms that recommend price changes for selected products at some level of frequency.”

“Despite the competitive advantage that dynamic pricing can confer, few omnichannel retailers have developed this capability. Some are only now starting to explore the potential of dynamic pricing. Other retailers conducted half-hearted and poorly planned pilots that, unsurprisingly, had little impact and thus failed to get the organization’s buy-in.”

This suggests two crucial things: First, traditional retailers have the chance of gaining a first-mover advantage since their rival counterparts are either not doing it at all or perhaps not doing it right. Second, dynamic pricing is not as hard to implement as everybody thinks it is.

The process starts with the cleansing and the organizing of enterprise-wide data. Smaller businesses will find it easier to do so and probably do it in-house. As for the medium and large-scale retailers, the unstructured data can pose to be a challenge as there is lots of it.

Social media sentiment analysis can help you understand where your business is today, and the areas where improvement is needed.

More and more businesses online are veering around to the fact that if they have to remain competitive, the one thing that will keep them ahead of the pack is a complete understanding of their customers. A customer’s identity resolution is like the Holy Grail for any business, especially in today’s competitive world. Know what is identity resolution and how it works. What are the key benefits of identity resolution?

A single unified customer profile is of paramount interest to businesses today. Identity resolution is the way of attributing customer interactions with your business across all touchpoints. Also, let’s not forget that in the last few years, the number of touchpoints customers can have with your business has simply exploded.

Want to know about the customer journey and customer identification? Fill up this short form and allow our experts to talk to you.

In a recent report, Forrester has described identity resolution as, “The process of integrating identifiers across available touchpoints and devices with behavior, transaction, and contextual information into a cohesive and addressable consumer profile for marketing analysis, orchestration, and delivery.”

So far, website cookies alone would do the trick where identity resolution was concerned but consumers are no longer shopping only on their desktops. In fact, more and more of them are now taking to buying from their mobile computing devices. That, and new data privacy laws have made the browser cookie passe.

What is “in” now instead is cross-device Identity resolution tracking. This is a process of collecting and combining data around a single customer in a way that links all his/her devices used back to him/her.

Why is cross-device tracking gaining importance? It is a fact that today, the average person owns multiple devices connected to the World Wide Web. Eg: laptops, smartphones, smart TVs, game consoles, etc.

Device tracking allows marketers to confirm which device and channel were used when a service or product was eventually purchased – whether it was a desktop, mobile, and whether it was from an e-commerce site or a social media channel.

With that, what has effectively happened is the e-commerce company or retailer has also managed to create a “unified” picture of its customer. The process is called “Identity Resolution”. Identity Resolution is the method in which certain unique “identifiers” are used to “connect” all the actions of a buyer to create a single, unified, real-time, customer identity.

So what are these identifiers? The location, the browser used, the device used, the platforms, and the channels, all of these are identifiers that help link the same person, irrespective of the device or channel used. Once a single customer’s identity is “resolved”, it becomes far easier for the marketer to serve up offers to him/her.

Because of Identity Resolution and customer data platform (CDP), each customer can be served up a personalized and unique brand experience.

All about cross-device tracking

So, for the reasons stated above, more than cookies, marketers these days prefer to use cross-device Identity Resolution tracking to maintain a complete profile of every client. Essentially, the latter allows the collection of data and its linking in a way that all devices used by one person are tracked back to him/ her.

The importance of cross-device tracking lies in the fact that it enables business teams to understand if a particular advertisement served on the desktop first resulted in a sale on a mobile; both devices are owned by the same person.

But here’s where things start to get a little tricky. There are two types of cross-device tracking – deterministic and probabilistic tracking – leading to two types of identity resolution – probabilistic and deterministic.

While both these methods involve complex matching across millions of data points as well as access to ALL the digital and device data, depending on the technology and data sets, they can deliver one of two types of matches.

Deterministic matching

Under deterministic matching, using a deterministic connector like perhaps a hashtag, email address, or username, the records of a particular customer are matched. This approach works best with first-party data.

Why first party? Because it involves the use of personally identifiable information of a customer like his/her email address, home or work address, telephone or credit card numbers, etc. At the end of this exercise, there remains no doubt about the identity of the customer.

Here’s an example: If John Doe uses his email address and logs into his email on his desktop, then uses the same on his Tablet, deterministic matching will show he is the same fellow. Deterministic matching is considered to be more perfect and takes the guesswork out of the tracking game.

But here’s the thing: although a more accurate matching method, it cannot be implemented by all businesses. One reason for that is because of the kind of resources it draws on, and because of the humungous amount of data, implementation is not possible for all the companies. So here’s where probabilistic matching comes in. The other factor that poses a hurdle in the implementation of deterministic matching is that it requires concrete identifiers like social security numbers or driver’s license numbers. But many a time, some companies do not need such information. Or, even if they do, consumers may refuse to submit such sensitive information.