Benefits of an Effective Data Strategy
What are some critical considerations for restaurants seeking to implement an effective data strategy?
Restaurants should be looking at all available insights and data to best understand changing consumer patterns and trends affecting their business, as well as enabling and informing so that they can make strategic decisions that drive growth and increase market share. An effective data strategy considers the critical value of third party, unbiased data sources such as human movement and audience data, that allows restaurants to get insights into consumer behavior they don’t get from their first party data. Restaurants must be able to answer questions like: Who's dining at what location? What time of day are they dining? Are my customers going to my competitors across the street? How can I make their experience better? Having these important data sets and insights answered in order to make better strategic decisions in regard to how a restaurant operates is paramount. Additionally, restaurants also need to obtain insights with their customers in regard to what they are doing when they're not engaged with their brand, like where else are they eating, shopping and visiting, as well as what that greater audience looks like– delivering these crucial insights is where Near truly expedites and gains value for its customers.
Can you share some examples of customer insights that restaurant operators should be attempting to leverage?
Restaurant operators are looking for dining out patterns and analysis to make better operational decisions. For example, one of our coffee QSR customers had extremely heavy traffic during breakfast hours pre pandemic, yet during the pandemic, they saw a dip in that morning traffic because people weren’t going into the office anymore. Having the ability to measure the patterns of people coming into your stores, the people going to your competitive brands, and being able to track performance at a chain level versus competitors is extremely important to leverage. For example, if you run a fast casual restaurant, you’ll also want insights as to how many people are going over to your competitor (and not just your own restaurant). You’ll want to track patterns and leverage insights such as whether your customers are engaged with your brand in the particular moment that they're dining with you or find out where they’re going outside of your restaurant, and what are they doing. With unexpected customer insights regarding the coffee QSR, they were able to make up for the loss in the morning traffic by finding out that people working from home now went out to get their daily coffee in the afternoon, versus the morning. This unexpected insight was found using our platform, resulting in the ability to make better business decisions, based on the unexpected new insights of when people were getting their coffees.
The other item restaurant operators use Near for, whether they're small chains or big franchises, is trade area analysis. These insights tell us where to open a new restaurant or mini mart– for both location and expansion opportunities– there are tons of great opportunities to look at this type of data, to not only run your current business more efficiently, but to also expand it very efficiently. Historically, human movement and location data have been used (and is still used) very well for market planning, trade area analysis and gap analysis. Today, it's becoming even more valuable on the guest insights part, which takes us back to understanding not only our own customers, but our competitors' customers, and other people that we're targeting to grow market share.
Can you speak to the benefits of segmented customer targeting? How has data science enabled better customer targeting?
Understanding patterns of human movement in combination with demographics, as well as an understanding of who your audience and buyers truly are is incredibly powerful data to have in order to make the right strategic decisions. Near not only combines these important data sets, but also curates the world’s largest source of intelligence across people, places and products at a scale that is surprising to most of the companies we work with– 1.6 billion unique user IDs, across 70+ million locations, and in 44 countries to be exact. But it's not just about having the data and being able to provide strategic data sets; it's the partnership that we have with our customers when we aggregate these data sets and sources with our customers, because we use the learnings to increase the confidence through our API-driven model.
For example, with Google search, every time you type in a search query, your computer gets smarter on your search patterns– that's exactly the way it works in our data universe. The more data we bring in from different customers, the more that our AI-driven data science model makes that data smarter. Every customer in our data universe benefits from that, so data science plays a huge role in our model. Additionally, the combination of not just the operational data for the operator themselves, but being able to look at the audience data, as well and combine some of the marketing decisions is key. For example, if I know who's going to a restaurant at a particular time of day, I may change certain patterns about how I do my marketing– for example, do I put up a billboard in a certain location, or do I run online ads at a certain time of day? There are very exciting opportunities with respect to what data science is bringing to the table, with the combination of human movement and audience data.
Is it possible to have a data strategy that bridges online and off-line?
It’s absolutely possible to have a data strategy that bridges online and offline data intelligence. This is exactly what Near offers, and is the way every modern marketer should be thinking– to combine the offline and the online experiences. Near bridges both of those universes in extremely practical ways, so that you can get insights whether your people are online or offline. We have a platform that allows you to combine your first party data (people visiting your website), with really powerful third party data or intent data, so that you can make decisions about the kinds of campaigns and reach you want to have, to acquire new audiences and better serve existing customers. It must be a combination of the two for competitive companies today, it's not an either or, it never has been. We make that a no brainer quite candidly, and have an amazing platform, both on the operational and marketing side to help buyers with a more comprehensive understanding.
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