5 Types of On-Demand Analytics Your Customers Desire

Business leaders spend a lot of time talking about how customer analytics can boost profit and productivity, and rightly so. You can use data about your customers to improve their experience and your efficiency and profitability.

But some of that same data can also be useful to your customers as they make purchasing decisions.

Customers want—and expect—personalized experiences. They want to be treated as individuals and they want their voices to be heard. While those things have always been keys to good customer service, they look a lot different in today’s digital economy.

How different?

Just ask two of America’s favorite brands: Amazon and Netflix.

A Tale of Two Brands: How Amazon and Netflix Transformed Customer Experience

Every decision Amazon makes is based on data, from the color and placement of the buttons on the website to which new products and ideas make it to production. Their goal is to make the customer experience simple and straightforward (hello, One-Click shopping). Amazon was also one of the first online retailers to position customer feedback data in the form of reviews as a key part of the decision-making process. Here are just a few of the ways Amazon customers benefit from data:

* Reviews
* In-stock and Out-of-stock notations
* Product recommendations based on purchase history
* Product recommendations based on what other customers have purchased
* Shipment tracking

But these aren’t the most exciting ways Amazon uses data. The company has always been known for embracing innovation in unique ways within its culture. That ideology has given us gadgets like Alexa, Echo, Kindle, and even dash buttons in your home for quick reorders.

All of these capabilities revolve around one concept: obsessing about the customer. Amazon has set a high bar in terms of customer expectations and it has transformed the way we think about online shopping.

And there’s another company that’s doing the same thing for video streaming: Netflix.

When you log in to Netflix, you have immediate access to a highly personalized, customizable selection of content based on your past behavior. Netflix also continues to improve the customer experience with innovations like automated preview videos that play when you scroll over a title.

Netflix has faced off with some powerful competitors like Blockbuster and cable television, but its relentless commitment to following the data has transformed the way we consume video content by creating unforgettable interactions.

Now, you may be thinking that these examples don’t apply to your business, because you sell widgets instead of streaming videos. But the reality is that just about every customer you encounter sets their customer experience expectations based not on your competitors but on the best-in-class examples all over the market. So if you don’t deliver a Netflix or Amazon type of experience, you’re going to disappoint.

What Do Your Customers Really Want to Know?

Amazon and Netflix have both built their empires on data. They use data in unique, powerful ways to serve people. And that mindset carries over into any industry, from manufacturing to technology to ecommerce.

Let’s take a look at five types of on-demand analytics you can offer customers to improve their experience with your brand.

1. Product Supply

High demand for specific products is great news for sales, but frequent out-of-stock notifications get frustrating for customers who need an item right away. You can use real-time data analytics to quickly pinpoint out-of-stock items and let customers know when their orders can be filled. You can also send notifications to customers when out-of-stock items are available again or let them know about last-chance opportunities to buy an item that is being retired.

This will require you to integrate your customer-facing systems with your product-management or ERP system, which may be a big challenge. But it’s essential toward meeting customer expectations.

2. Purchase History

Purchase history is one of the most reliable ways to make product recommendations since past purchases tend to be accurate indicators of preference.  For example, Shoe Dazzle collects customer data—including both purchase history and personal preferences—to develop a style profile and make targeted recommendations.

Many of the new on-demand subscription clubs like Stitch Fix also use data to give customers more of what they want.

You can also keep track of what customers have purchased and send notifications when it’s time for them to restock. FilterEasy does this for home air filters as one example.

3. Customers Like Me

Since Amazon made the customer review a standard expectation, customers increasingly want to know what customers like them think about a product or service. There are several ways you can answer that question:

Product reviews and ratings

Reviews and ratings serve as “social proof” that your products meet customer expectations. In just one or two clicks, customers can rate a product, contributing to an essential trust-based relationship.

Review filtering

Ever get tired of scrolling through pages of customer reviews with no way of knowing which ones are relevant? You can make reviews more valuable to your customers by adding filters so they can search feedback from others with similar demographics or purchase habits.

Aggregated customer data

Collecting data from a wide swath of diverse customers makes it possible to offer recommendations about the best product choice in various situations. It also helps your customers learn from others who have had similar experiences.

Product bestsellers

Showcase products with high conversion rates so customers can see what others have found to be valuable. You can combine with a “Frequently Purchased Together” feature to support the decision-making process.

4. Usage Information

If you offer a subscription service, your customers may benefit from tracking their usage over time and knowing how their usage compares to others. Duke Energy, for example, includes usage history and comparative usage data in their monthly statements. In their personalized home energy report, customers can see how their electricity usage compares to other similar homes in their area, helping them gauge how “green” they are and pointing out ways they can reduce energy costs. 

5. Shipping Data

Shipping data contributes to customer satisfaction across the board from ecommerce retailers to industrial transportation companies. Knowing when an item shipped, where the shipment is, and whether delays should be expected helps set expectations and avoid frustrations.

Shipping industry companies can drill down even further into the data to give customers greater control over buying decisions. For example, you can track how often a customer ships, what days and times throughout the month they typically ship, and whether shipping patterns remain consistent over time or tend to cluster around specific events or holidays. You can use this information to reach out to customers when they need your services most or make suggestions about how to cut costs by combining shipments for better value.

Conclusion: The Right Data At the Right Time

As with any data initiative, the key to improving the customer experience with data is to determine what information will help the customer achieve their goals. Data should support the building blocks of a positive customer relationship by contributing to trust, usability, and decision-making. Bombarding people with too much data, by contrast, contributes to information overload and makes the decision process more difficult.

But how do you know which data will be most helpful to any given customer? It starts with understanding them and knowing where they are in the buyer’s journey. Use interviews and other tools like customer personas to flesh out your target audience, and learn to use data in different ways to support customers in the research phase, the comparison phase, or the purchase phase.

For example, a customer who is ready to make a purchase may want to see data about shipping times and backorders, while a customer who is researching products may want to browse reviews and ratings.  

The right data at the right time: that’s your goal. By using data to simplify your customers’ experience with your brand, you can establish long-term, loyal relationships based on trust, and that’s the Holy Grail for any customer interaction.

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