Upcoming Webinar | Insights from the 2021 dunnhumby Retailer Preference Index for U.S. Grocery
The Great Recession programmed lasting value-consciousness into the minds of consumers. How might COVID-19 rewire us again?
The fourth annual dunnhumby Retailer Preference Index for U.S. Grocery (RPI) sheds light on what makes a retail winner, and how the pandemic has impacted consumer shopping behaviors. Known as retail's equivalent of the Gartner Magic Quadrant, the RPI surveyed about 10,000 consumers to understand what's driving customer preference and rank the top 57 grocery retailers in the United States.
Join dunnhumby CEO Guillaume Bacuvier as he dives into the latest study, revealing the levers for success, and which retailers are winning the hearts, and wallets, of shoppers today.
In order to reflect on how the grocery world changed in 2020, we have changed how we calculate our overall Grocery RPI score. Given the historically unique metrics we've witnessed in the economy, the restaurant industry and the grocery industry, along with the rare influence a global pandemic has brought to consumer behavior, we're viewing grocery success in 2020 through a different lens than we viewed grocery success in prior years.
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Do you actually TRUST your Customer contact data?
Are you looking to increase your contactable Customer base? How much money are you losing on incorrectly identified Customer communications? Throughout our 30 years of big data experience working with clients across industries around the globe, we have found that maintaining contact through relevant Customer engagement is a crucial component of putting the Customer First.
Essential to preserving contact data is ensuring that you have the most up-to-date information from your Customers; not an easy task. On average, people in the United States will move an average of 12 times in their lifetime. United States Postal Service data indicates 14% of the population change addresses annually. As email contact has grown, it's important to note that, on average, 30% of people change their email addresses each year. This is driven by ISP or job changes, or just to stop being spammed. As people move away from home phones to primarily mobile devices, phone numbers are stabilizing as consumers maintain the same numbers through physical moves.
Contact data maintenance also includes an effective and trackable process for removing Customers who "opt out", unsubscribe or otherwise request to not be contacted. Beyond Customer fallout for not honoring their request, regulations such as GDPR and CCPA can deliver fines as high as €20 million, or up to 4% of the annual worldwide turnover of the preceding financial year (whichever is greater), for any violations.
So, how are you collecting and managing sensitive, frequently changing Customer metadata? These three questions can help you perform a quick data health check for your business:
- How flexible are our Customer data platforms? Can multiple departments use the same Customer master data profile?
- What are the accuracy requirements for each of our communication channels?
- How unique is our Customer data asset and how valuable is it to our company?
Here are the most common data management options we encounter across industries:
Maintaining Customer information manually through an internal data team can be time-consuming and costly. It may require Customers to update their information online or through a call center, with an internal data team to validate the changes, and your Customer engagement team to be made aware of the changes so they can update their downstream systems. If you are in contact with your Customers on a weekly basis, this process will need to be on-going and thorough to accurately capture the data changes.
Many third-party CRM systems and databases exist, often removing the manual steps from this process and may even automatically update Customer address information via online sources. In many cases this information is based on publicly available data or the USPS' address tools. However, these updates can verge on being "creepy" to many Customers. Automated systems do remove many of the manual touch points for your teams, but the information is then strictly provided by the third-party databases and processes. Additionally, downstream systems often still require updates from these tools to maintain the most correct Customer information across your data landscape.
While there are some hybrid models of options, here are the main pros and cons we have identified for the primary methods:
|Internal Pros||Internal Cons|
|The fastest method if you own and manage your data ingestion platform||Managing a metadata repository tied to your website or mobile platform may require significant improvements in your front-end systems and teams|
|Your internal security can ensure that personal data standards and protections are maintained||A true "Customer master" repository will require significant resources, a robust data governance structure and regular audits for both security and data accuracy|
|The easiest method for maintaining your Customer opt-outs and communication preferences||If there is a data breach from your systems, your company is 100% liable for the breach|
|Platform and tool agnostic. An internal "Customer master" repository can serve as a single source of truth for Customer data within your organization|
|Leverages the information provided from your Customers which in practice should be the most trusted|
|3rd Party Pros||3rd Party Cons|
|Removes significant pressure from your internal teams and systems as you are pushing the process to the 3rd party||May require you to maintain your own Customer opt-outs and communication preferences external to their platform|
|If the data resides on and is consumed from their systems, on-going security becomes less of a concern for your internal teams*||May not allow Customer provided information to be captured or maintained|
|Can be a very accurate source if they are leveraging governmental and legal databases||May require the use of their specific software and technology, limiting the ability for your organization to create an internal "Customer master" on your own databases and downstream systems|
|May be updated on a real-time basis from their systems||You are tied to the 3rd party data match and update process dependencies. Additionally, some companies limit the daily number of requests or queries|
|APIs and other data integration points with the 3rd party may be made available ensuring that all internal teams have the same "Customer master"||Are they consuming publicly available data (ex. mortgages and legal proceedings) or are they using some large unmanaged database to match Customer details and data?|
|How often are they confirming the accuracy of their data? Example "John Smith" may simply be a typo from years ago or it could be correct. How do they confirm accuracy?|
|*If the 3rd party or their associated processors breach your Customer information, you may still suffer reputational and financial consequences|
Regardless of your chosen data mastering methodology, the Customer's preferred data should always be treated as the "most trusted," as this is the data your Customer is asking you to use. We recommend prioritizing Customer-provided data over other sources, only falling back on alternate sources if there are issues with Customer communications.
dunnhumby can help your company develop a comprehensive Customer mastering solution, regardless of your existing CRM process, technology or vendor. We have spent the last 30 years working with Customer data in many different stages of maturity and complexity. Through this process, we have developed proven best practices to collect and maintain your Customer metadata. If you are interested in discussing Customer mastering or Data Consulting, please reach out to your dunnhumby client representative or Contact Us.
In my last post, I posed five questions to retailers to help them determine whether they're ready for a customer-first mindset. Now, I'd like to challenge the retail basics that seasoned retailers were trained on, and suggest instead a new customer data science approach.
"Retail is detail" is common industry wisdom, and it means that achieving success is subtle and difficult. Success in any field demands practice and experience, and so it is little wonder that many senior retail and brand leaders and managers have vast years of involvement, and that most have grown up through the business in progressive steps.
Accordingly, business decisions are heavily based on experience, and more often on personal memory of choices and executions and how a thing has traditionally been done. As Chris Foltz, director of operations at Heinen's Fine Foods, told me, "Our industry, and our company, was very opinion-based, albeit expert opinions. We realized early on that we needed data on customer needs, customer satisfaction and customer buying behavior to improve our decision-making. As we adopted this metric-driven approach, I believe we prioritized our investments and effort to deliver a better customer experience."
These are a just few of the things that most retailers absolutely know for sure:
- We must acquire new customers in order to grow our business.
- Price-sensitive and "cherry picker" customers are not profitable. The competition is welcome to them.
- Customers are different in every region of the country. There are also differences between urban and suburban shoppers.
- Loyal customers are already giving retailers most of their spend in the categories offered.
- Weekly flyers and promotions always drive footfall and sales.
- After all these many years in the business, we know what customers want.
Why What We Know About Customers Just Ain’t So
The old axioms are no longer factual because customers themselves have dramatically changed, in their needs, expectations and experiences. Separating fact from fiction—and business truths from myths—will change how the business sees itself and how it will make decisions. The following are some of the new truths of retailing in the 21st century:
- Expanding share of wallet from customers who are already "loyal" can better optimize growth.
- Loyal customers need more love and investment than new customers.
- Retaining loyal customers and reducing churn among "opportunity" customers can drive more growth than acquiring new customers.
- Price-sensitive customers are often more profitable than other segments because their basket mix includes more private label products or higher-margin portion sizes.
- Behavioral "buy-o-graphics" and intended trip missions matter much more than demographics or geographics.
- Customer segments are typically distributed variably within geographic regions or zones, but all customer types exist in all stores.
- Store clusters built upon customer dimensions are more useful to operations and execution than store groupings based on geographic zones or volumetrics.
What We Know for Sure Can Fit on a Post-It Note
Agility in retail can only be maintained by understanding customers and using data in all available quantitative and qualitative forms. Here's a personal story to illustrate:
A perception-based research tool measured one retailer's progress against factors that customers themselves had said are most important to them. Before the first customer perception report was published, I set out to learn how the customer ranking compared to the rankings that the senior decision-makers would assign.
The regular weekly senior team meeting brought together many of the wisest and most seasoned leaders in the business. After briefly introducing the research methodology, I asked the team to list what factors they thought customers would list as important, and in what order they thought customers would place them.
Not surprisingly, each merchant tended to rank factors in their department higher on the list than those for other parts of the store. Although little agreement was reached, a compromise ranking was eventually defined.
Comparing our list to the customers' list revealed spectacular differences; leaders had listed most of the same elements as did customers, but in completely the wrong order. That day, the team experienced a true epiphany—they realized that "we didn't know what we didn't know."
The lessons learned were:
- Humility gained in discovering that "we don't know what we don't know" empowers the customer-first journey.
- To become more relevant to customers, we must become fact-based deciders and activators.
- Using customer data well creates true consensus and inclusive action.
In summary, “In God We Trust” ... all others must bring data.
David Ciancio is global customer strategist for Dunnhumby, a pioneer in customer data science, serving the world's most customer-centric brands in a number of industries, including retail. David has 48 years' experience in retail, 25 of which were in store management. He can be reached at email@example.com