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How Walmart and Disney Use Data to Build Better Products and Experiences

Written by

Team Egen

Published on

Feb 19, 2019

Reading time

6 min read

  • Data & Analytics
  • Business Strategy

Why is Disney investing billions of dollars into a wristband and Why does Walmart care when it’s going to rain? The answer to these questions can be boiled down to one single word: data.

An executive’s guide to implementing and scaling data strategies

Why is Disney investing billions of dollars into a wristband?

Why does Walmart care when it’s going to rain?

Why does Target launch their swimwear collection in the winter?

And since we’re asking the hard questions: Why is it that some Ice cream parlors consistently sell more Ice cream in the winter than they do in the summer?

The answer to many of these questions can be boiled down to one single word: data. Data informs these businesses on how to make proactive decisions that, at first glance, seem illogical.

So, let’s get these questions answered. I know you want the Ice cream answer first, but let’s start with Disney.

Disney’s MagicBand allows you to enter their parks, unlock your hotel room, purchase meals and merchandise, and skip the wait on rides all from your wrist with an RFID bracelet. That’s what you call a “magical experience.”

But that’s not the most magical part about the MagicBand.

The real magic is that Disney uses this data to make your experience even more magical than it is now. You know that churro stand you walk all the way across the park to get every single night you’re in the park? Don’t worry, they will eventually move it closer to where you’ll most likely be at 8 p.m. because they have the data (from the band) that shows you and your family, as well as a group of others similar to you, are doing the same activity nightly.

End result? You’ll get your churros faster, and Disney gets more of your money. Win-win for everyone.

That’s the power of having a clear, effective data strategy. Which leads me to this question that we ask our clients often:

How would your business change if you had access to the right data at the right time?

According to an Accenture study, 79% of enterprise executives agree that companies who do not embrace Big Data will lose their competitive position and could face extinction. Even more, 83% have pursued Big Data projects to seize a competitive edge.

The answer is the same whether you’re a 10-person startup or a Fortune 100 company. It can be the separation between growth and death.

We uncovered three major levers that can be uitilized when implementing an effective data strategy.

Lever #1: Uncover hidden business insights and new business models

“No matter how often we say we’re creeped out by technology, we tend to acclimate quickly if it delivers what we want before we want it” (Kuang, 2015).

The most traditional way to get data insights is to perform a survey. You ask customers for feedback, they give it you, and you make adjustments based on that feedback.

However, the data collecting game has changed, and the traditional survey method might not always uncover the right insights. Disney doesn’t put out a survey to ask how often someone purchased a churro in their park because they already have the answer due to the MagicBand!

Gaylord Hotels is a great example of a company using public data to improve their referral strategy. The company undertook an analysis of social media data, looking at every instance where the hotel’s name was mentioned by customers in public platforms like Twitter.

Customer recommendations and praise were examined for any clues as to what had spurred them and at what point in the customer’s stay. The results were illuminating. A short list of just five elements of the guest experience seemed to have the greatest influence, and all of them took place in the first twenty minutes after arrival.

Imagine what you could do with this specific takeaway — that the first 20 minutes are the most critical part of whether a customer refers you or not. Would you invest in more check-in staff? Offer a cocktail for every guest that walks in? Reduce the check-in time?

Lever #2: Send hyper-personalized and targeted marketing messages to the right people at the right time

Why does Walmart care when it’s going to rain?

Have you ever gotten an ad that was so unbelievably spot-on to your needs that you questioned how in the world the ad knew your situation? You didn’t search anything, and you never talked about it.

It turns out that knowing when it’s going to rain, snow, or if there’s a hailstorm coming your way, is an opportunity for Walmart to offer hyper-focused advertising messages based on the weather or to reduce spending on days when they know foot traffic will be slow because of the weather.

Just like the guy who sells umbrellas outside subway stations when it’s raining, Walmart recognizes that weather deeply impacts customer purchasing behavior. Walmart and other leading retailers use this real-time data feed from The Weather Channel to feed into their programmatic advertising model.

The real interesting part, however, is that The Weather Channel (TWC) is offering a service outside of their normal wheelhouse.They created a brand new business model centered around their data offerings.

TWC’s data scientists work with retailers to identify how the weather will impact their sales, which informs the retailer on how much (or less) resources they should apply towards advertising and merchandising.

That’s the power (and future) of data.

Lever #3: Make better business decisions with the right context

If we pulled in financial record data from every single ice cream parlor in the world, we would find out that some of them consistently sell more ice cream in the winter than they do in the summer.

Without any context to the data, you would be royally confused. What is it about these specific ice cream parlors that makes them sell more when it’s freezing out than when it’s hot out?

If you add location context to the data, you will find that the only ice cream parlors who sell more ice cream in the winter than in the summer are the ones located on a university campus. Simply put, most of the students go home for the summer and there is less foot traffic, which results in less sales.

This simple, but effective example is how context can help your business grow.

A great enterprise example of contextual data in action is Target. For years, Target launched their swimwear collection in late spring/early summer. However, after analyzing the data, they figured out they were missing out on a key piece of context: college kids preparing for spring break.

“Our data showed us that our guests were talking about swimming for two months without us,” said Kristi Argyilan, SVP of media and guest engagement at Target. Even though this required a major shift in supply chain management and marketing, it’s important to time the flow of merchandise based on who is buying when.” [source].

Rent the Runway is another great example of contextual awareness. Their data shows that accessories are only purchased AFTER the dress has been purchased.

Understanding the customer’s emotional state was also important for add-on sales. The company learned that customers were more likely to be interested in additional items like shoes and accessories only after they had found a dress. “Post-dress acquisition, you can see the customer is in a different emotional state and that’s when we tell them that these accessories can go with this dress,” Subramanian added. [source]

At a higher level, these examples seem fairly straightforward. However, in a business setting, you will consistently see that context is almost never brought into the conversation. Do it the right way, and you will see an improvement.

How Egen can help you accelerate your data strategy?

For the past decade, we’ve helped well-funded startups and large brands scale through our extended product development teams. Based on this experience, we built re-usable development components for every product integration possible so we didn’t have to reinvent the wheel every time. This turned into Kernel, a platform that we build every single product on.

This platform significantly increases our time to build, deploy and test data-intensive products that generate value for our customers. We do this through our data modernization pilot program:

6-Week Data Modernization Pilot Program – Jointly with our customers, we assess the value of their data, and look into how we can solve various business issues with this data. The result could mean new insights into how you can better market to your clients, new mobile & web products that serve your customers needs, or a brand new business model that generates revenue from your data.

Assessment / Creative Discovery – Through several workshops, our team uncovers key customer centric use cases, and gain an understanding of how your data can fuel these use cases for an advantage in the marketplace. We’ll look into your core service offerings as well as investigate how your data can fuel growth in new business models.

MVP & Rapid Prototyping – This is where our real advantage comes in. Because of our proprietary data integration platform, kernel, we build prototypes based off the use cases quickly and get them in the hands of your team. This will allow every executive and team member to see first-hand how data can provide a business impact.

Minimum Valuable Product Execution – Post prototyping phase, we’ll gather all the feedback and solidify which products / use cases can provide the biggest impact on the business. We’ll help you flush out the business model and create a go-to market plan.

This approach – Think big, test small, move fast has proven to be a trusted approach to bringing real value to unknown and complex subjects.

Download our white paper on How to use Data to Build Better Product Experiences.

What has data done for you lately?

That’s the question we challenge you to ask yourself every morning. You have opportunities just waiting to be discovered, marketing that can be more hyper-focused and personalized, and the ability to scale your learnings through data engineering and automation.

Have any questions? Feel free to reach out to us.

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