Using shopper data to develop insights that drive better decisions is an approach many modern retailers follow, but how many manufacturers are really reaping the rewards that granular shopper data can provide…
With many sources of market data available and product sales data, manufacturers may feel that they have sufficient insight to understand which of their brands are performing well and which may need intervention. But to get a true understanding of who is buying your products - why, how and when - a far more granular level of data is required.
Here are some examples of how shopper insight can give brands deeper knowledge of consumer habits in relation to their products:
Your promotions – are they really working?
If you're running a promotion for one of your products, you'll hopefully have sales figures which show whether there has been an uplift in LFL sales during the period of the promotion. An increase probably can be attributed to the promotional campaign. So far so good. But what else do you know about that promotion campaign which could help your future marketing activities and investments? Who is buying your product on promotion? Are you cannibalising sales from existing shoppers who would have bought it anyway at full price? Are they 'pantry loaders' who are buying in bulk, bringing their spend forward? Is it one shopper buying 3 products, or 3 shoppers buying 1 product each? Are you keeping and converting new customers who buy your brand on promotion? By knowing more about who your shoppers are and what motivates them to buy your product, you'll be able to steer your marketing spend more effectively and avoid wastage.
Brand loyalty – does it really exist?
It's one of the biggest challenges for brands in the face of changing consumer habits and proliferation of channels to purchase: generating and maintaining brand loyalty amongst shoppers. Common beliefs that brand loyalty no longer exists and mass marketing is required to keep continually topping up the funnel with new shoppers in order to keep brand sales buoyant are hard to dispute, unless you have data to prove otherwise. Yet if brand owners don't understand who is buying their product and where there might be headroom for growth, they will struggle to create the right environment for this to happen. Industry sales data might tell you what your market share is, but do you know what your shopper's repertoire is? Are they only buying your brand or buying competitor brands within the category as well? How frequently are your shoppers making purchases? What events or factors are prompting their purchase decisions: pack size first, then brand? Or the other way around? Understanding switching, cross-shopping and retention behaviours are key KPIs you can measure from granular shopper insights.
Giving your new products the best chance of success
New product development is viewed as a great way to encourage existing shoppers to buy more of your products, and attract new shoppers to your brand, yet the failure rate for NPD is remarkably high. Convincing retailers to give up shelf space for your new product can be difficult, and if it doesn't bring in the expected return on investment for both parties, retailers will be quick to de-list it. Understanding category dynamics and the likely universe of shoppers who have the highest propensity to purchase will create a solid foundation for your NPD. Using shopper insight can help you determine what proportion of the retailer's customers you should target with your new product – based on previous purchase behaviour and basket mix. Who has a history of trying new products and sticking with them? Getting an early read of 'trial and repeat' behaviour can help with targeting.
Category growth and shopper Needs
Brands and retailers can both be winners if they work together to grow categories. But understanding shopper needs is vital in making this happen. Key questions you'll want to answer are: What are the gaps in the range? Are there any un-met customer needs which could point to opportunities for growth? What is driving loyalty amongst shoppers within particular categories? Did your promotion or new product launch drive overall category growth? What's the relationship between certain products in the category, and which matter most to shoppers?
A great example of collaboration between manufacturer and retailer to co-create a promotional plan to drive sales and category growth can be viewed here.
There are many issues that will undoubtedly be keeping manufacturers up at night – generating and keeping brand loyalty, creating excitement for shoppers in a sustainable way that doesn't damage your brand (overpromotion), driving growth through innovation (NPD) and increasing brand penetration through retail outlets. The great news is that shopper insight can play a key role in solving these issues and giving your business competitive edge. Getting access to more granular data is the starting point…
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There are lots of stories that start with how retail used to be. As some of the great American department stores fade away, they are reminders of what was once an elegant and successful combination of service and selection. Corner drugstores were also iconic centers of community and consumption, offering a broad spectrum of products, and providing a place to gather due to the nearly ubiquitous, but now effectively extinct, soda fountain.
The special connection between these types of businesses and their customers transcended the products that were sold. It was, in effect, 'experiential', a term used often today to describe where retail is going rather than where it came from. Advice and guidance were paramount in creating a great experience for the customer. And it's this human aspect which will be the great differentiator in retail today, particularly for pharmacy.
As retail starts to swing away from the commoditized, big box, 'self-serve' models which have dominated in recent decades, many retailers have failed to address changes in consumer behavior as products, technology, and general shopping preferences evolved. In 2017, US retail closed approximately 9,000 stores with 50 chains filing for bankruptcy[1]. The competitive pricing and selection of Walmart and online retailers undoubtedly present a difficult challenge, yet some retailers, (and specifically Pharmacy retailers) are sitting on un-realized assets which could differentiate their offering and develop a loyal bond with their customers. Here are the areas we see having the greatest opportunity:
The first reality is that mediocrity is a retail killer. There is simply not room for 'average' anymore. In today's retail world, selection is nearly infinite with omnichannel, but with all that choice comes inevitably, a greater need of guidance. Do peer reviews and likes from unfamiliar individuals, (who may or may not be a real person) really do the job? Only if you're buying a truly commoditized product and you have absolute level of certainty that it's the best decision based on a combination of factors most important to you.
With the tremendous development in technology and innovation; EVERYONE is striving to move away from commoditization to differentiate. No more is a bar of soap, just a bar of soap. It now has key ingredients of wheat and green tea, and is available in 27 varieties of color, scent, and size.
While much of this incredible variety does not always translate to bricks & mortar; quite a bit actually does. Walk down the aisles of a retail pharmacy, even a small one, and you will see the amazing assortment of products that exists today. Even in the more mundane categories. A typical US pharmacy has over 15,000 SKUs.
Faced with variety, choice and overwhelming quantities of information, customers are looking for guidance and service from someone who is knowledgeable, and someone they trust. The pharmacy occupies a special place at the crossroads of retail and healthcare. With the right service for the right products, it cuts through the endless suspect analyses and recommendations and provides a true connection between the customer and the place, the bricks & mortar location, that breeds trust and loyalty.
The true ace in the pharmacy hand is the pharmacological doctor on staff to be the spear-point to building that loyalty. In a 2017 Gallup poll, pharmacists were ranked as the 5th most trusted and ethical professionals in the US. Pharmacists have been in the top 5 of 22 listed professions for 15+ years, further reinforcing the value of that role.[2] With the right proposition for the customer, it's the human interaction that elevates physical pharmacy over any online competitors.
Bricks & mortar pharmacies are many times the most accessible point of contact, medically, for consumers. While the need for prescription guidance is considered a given, the opportunity being missed by many pharmacy retailers is extending personal guidance to its front end store products.
Through our work with retail pharmacies, we've seen that even in categories considered predominantly self-service, the customer is looking for assistance. Personal care customers in general, and the shampoo category in particular, benefits from assisted selection in 40% of transactions.[3] Understanding the critical categories and strategically designing the space to best utilize store resources will go a long way to providing customers the experience they seek, helping reinforce loyalty and generating greater sales. While this can be a challenge for retailers with hundreds of stores and millions of customers, clever use of insights from customer data can help the pharmacy provide superior service through individually crafted recommendations provided on demand when needed.
Tailored assortment, merchandising, and appropriate pricing and promotions built using customer data, will further build customer trust rather than erode it. Over time and through consistent execution, the pharmacy of the future will prove its value through developing the unique relationship between pharmacist and customer. And the humble corner drugstore will once again be viewed as a valued pillar of the community.
[1] https://www.forbes.comhttps://www.dunnhumby.com/sites/blakemorgan/2018/01/06/the-upside-of-a-retail-apocalypse
[2] https://news.gallup.com/poll/224639/nurses-keep-healthy-lead-honest-ethical-profession.aspx
[3] As observed through dunnhumby research
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What channels should you expect in interacting with your customer today? As technology, business and shopping habits evolve, it's more important than ever to understand how each customer shops – and how their omnichannel journey can be influenced by relevant and timely communications at every step of the way. Online and offline, at home and in-store – when customers are more accustomed to be engaged across multiple touchpoints in real time, marketers should respond actively.
Take a look at this infographic demonstrating why having an omnichannel strategy is so important, and highlights the growing complexity of the modern customer journey that retailers and brands must understand.
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Article originally appeared on Chain Store Age
Forget the headlines. Grocery stores are nowhere near extinction due to the battle between online and brick-and-mortar grocery stores. Although online grocery is now the fastest growing grocery channel with a CAGR of 19.5%, it represents only 2.0% to 4.3% of the $700 billion U.S. grocery market, and has a long way to go to dethrone physical grocery stores. According to IGD, the U.S. online grocery market was $23.9 billion in 2018 and is predicted to grow to $59.5 billion by 2023, still less than 10% of the size of the entire grocery channel.
Grocery stores are in fact in a new period of growth and reinvention. Although the Amazon effect is placing pressure on both brick-and-mortar and online retailers, it is also ushering in a future of transformative changes for grocery stores. Here are some of the changes coming.
Customer experience will be huge
In the future, stores will cater to shoppers' insistence on a seamless experience whether they are in the store or shopping online. Retailers will create experiences that easily guide customers through the store to make shopping trips faster and easier. For example, some stores are activating customer data and working closely with brands to create new in-store experiences that make shopping easier for customers including organizing product sections around consumer needs, such as gluten-free and organics, or moving ready-to-eat meals to the front of stores. Metro, Canada has created new in-store experiences in dairy, frozen food, and beverage and snacks.
Grocers will also be taking a page from retailers that are creating "experience destinations" based on the needs of their communities. For example, Raley's is building a new flagship store that "will emphasize healthy living and destination meal offerings, with key features including a loft dining area, wine tasting room, sushi and bakery departments and 25,000 square feet of outdoor seating."
Future shoppers' grocery store visits will be driven by a desire for inspiration in their leisure time, instead of just needing to restock their kitchens. They'll visit to experience new products in-person and via augmented reality, participate in cooking demonstrations, and enjoy activities like wine tastings.
Convenience will be center stage
Twenty years ago Jeff Bezos predicted that brick and mortar stores would survive only if they provided either entertainment value or immediate convenience, and that has proved largely true for grocery stores. Shoppers in the future will continue to be pressed for time and will want to shop at stores that are conveniently located, have the right variety of products to meet their needs, and where they can get into and out of quickly.
Before even leaving for home, the shopper's integrated smart home will help inventory what items need to be purchased and add those items to the list that is then automatically relayed to the retailer to prepare for the shopper for either home delivery or click and collect in store. Once the shopper arrives, the retailer will alert the shopper of real-time promotions that are based not only on their shopping patterns but also on other variables such as the weather. On a rainy day, a shopper may have soup coupons displayed on their phones, whereas on a hot day a shopper may have coupon deals for a barbecue dinner.
Once inside, shoppers can open a mobile app to enable personal pricing on digital shelf edges. They will also be able to scan and pay for their items with their phone. Before exiting, shoppers will also have "infinite" options available for home delivery or click and collect.
Grocery stores will shrink
While the superstores and hypermarkets still command the largest share of the customer basket today, future grocery stores will be one third to one half the size of what they are today. The average grocery store built over the last 10 years has a footprint of 45,000 square feet but newer stores are already shrinking with many closer to 20,000 square feet. Future grocery stores will be even smaller.
The stores will carry about 5,000 items compared to today's stores that have 45,000+ SKUs. The stores will focus more on local, regional offerings as well as on private brands. Dark stores will likely attach to the smaller footprint store from where products will be picked and staged for pickup or delivery.
Discount grocery shares will capture increasing market share
Beginning with the Great Recession, consumers have become very price conscious and have grown used to looking for the lowest prices for their groceries. And more than 10 years later, consumers remain very price conscious resulting in the price sensitive and low-income consumer demographic is the fastest growing demographic. So, it's not surprising that 2018 saw a 30% increase over 2017 in new grocery store openings according to JLL that were largely propelled by the number of discount stores openings.
Aldi opened 82 stores in 2018, accounting for nearly 16% of all grocery stores opened during the year.
Aldi alone opened 82 stores accounting for nearly 16% of all grocery stores opened in 2018. Over the next five years, the discounter will build 800 more stores and have just shy of 3,000 stores in the U.S. In fact, Aldi plans to be the third largest grocer – after Walmart and Kroger – by 2022. Trader Joe's, part of the Aldi Global family, also plans to add 25 to 30 new stores this year and due to its superior focus on price and quality was named for the second year in a row as the top-rated grocery retailer in dunnhumby's Grocery Retailer Preference Index. Lidl recently announced plans to open 25 more stores in the U.S. as it continues its expansion in the U.S. market.
Discount stores are the second fastest growing grocery channel next to online grocery and are expected to grow at a CAGR of 5.8% and will be $514 billion by 2022. With discount stores offering lower prices, private brands that consumers are growing to love, and with nimble stores to get into and out of quickly, it is not surprising they are expected to continue growing at a brisk rate in the future.
The robots are here — and more are coming
Robots, drones and other forms of automation have already arrived to a number of grocery retailers and more will be coming. Some retailers are already using automation and artificial intelligence to closely monitor inventory and picking in the warehouse and to make sure their inventories can be replenished within a day instead of weekly. Drones will also be used to hover above the aisles and scan inventory. In fact, Pensa, a startup based in Austin, drone solution that does just that is expected to be in stores by the end of the year.
Grocery stores will be automating routine and time-consuming tasks, to not only save money but also free up customer service people to engage with customers. Retailers that have built up troves of customer data through loyalty programs over the years will also be at an advantage. By utilizing video analytics and artificial intelligence, retailers will be able to predict customers' state of mind and then be able to make timely recommendations to customers as they shop.
Autonomous vehicles delivering groceries, similar to the ones Kroger has introduced, will also be in play delivering groceries to customers who don't want to shop in the store. And, robotic assistants like Giant Food Stores' "Marty" will be common place scanning shelves, identifying spills, and even scrubbing floors.
Online or offline, customers will demand an exceptional experience from retailers. And the best way for retailers to ensure they are creating the store of the future their customers want is to make sure they understand not only the technology on the horizon, but more importantly are listening to what their customers are already telling them through their data.
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With great customer data comes great opportunity. Today's retailers have access to more data than they've ever had before, and smart use of it can give them an invaluable competitive edge in challenging conditions.
But if you're thinking of developing a new data monetisation strategy, or overhauling an existing one, it's worth assessing your starting point first. Understanding the critical components of good data monetisation can make all the difference to the success of your strategy.
You'll also need to understand how your data will support the decisions you want to make and execute against, plus the role of CPGs in key decisions like ranging, promotions planning and in-store and online media.
The most effective data monetisation strategies are built on four key pillars. Get these in place and you can move forward with confidence.
1.Data
The best strategies are driven by insights into customer behaviour, not just sales data. Everything from how often they're shopping and how much they're buying, to how many premium products they're opting for. The more you know about what your customers are doing in-store and online, the more customer-centric the resulting recommendations will be. You can't build a data monetisation strategy that will transform your business on transactional sales data alone.
This means that the first thing you've really got to get in place is the right data. Ideally this will have been collected through a CRM programme, such as a loyalty card with a coverage of at least 50% of customer base.
Once collected, you'll get the most from your data by merging it into a single database. This means information from different categories and locations can be analysed together, creating a consistent data-driven customer language. You and your CPGs can then use this consistent language when talking about category and brand performance, and use consistent KPIs to track and measure success.
Used correctly, your data will provide a framework for shared workstreams to better meet the needs of your customers.
2.Culture
As we've discussed previously, the retailers competing most strongly at the moment are those who are putting customer needs first. If you have a customer-centric culture embedded from the top of your organisation to the bottom, you'll find it significantly easier to get the most out of data monetisation. This is because your whole organisation – including buyers, category management and insight teams, and merchandisers – needs to focus on understanding customers, not just sales and margins. It can't just be the responsibility of one team.
Monetisation strategies are successful when they equip the retailer and their suppliers with the insights to work together to achieve category level objectives. As a retailer, if your working relationship with your suppliers is already based on trust, transparency and collaboration, rather than the traditional 'them vs us' dynamic, you'll find this comes easily.
Some retailers have concerns about transparency – not wanting to share category insights with CPGs or fearing that doing so reduces their power in the relationships. But at dunnhumby, we always argue that the CPG needs to see the insights for the whole category, not just their product. This enables them to really understand how they can support the performance of the category and align their brand portfolio to meet this objective.
Together, you can collaborate to:
- Ensure trade planning focuses on promoting products that generate sales uplift for the category, instead of negotiating the funding of promotions
- Ensure range planning meets the needs of customers, rather than focussing on increasing space for margin-driving SKUs for a single brand
Processes are another area where retailers can give themselves a head-start. If you have a properly documented category management process in place that's compliant and used across your category teams, the tools of data monetisation will be much easier to use.
If you also bring CPGs into the process, you'll benefit from an external view, category expertise and a competitor retail perspective. Empowering one or two key suppliers in the category as 'category captains' can ensure you're making full use of their experience, resource and knowledge. When customer data is embedded into a work plan supported by an end-to-end, 'insight to execution' process, your successful customer-led category strategy will be easier to realise.
3.People
Is someone in your organisation leading the commercial workstreams related to your customer data? Your chances of success will be greatly helped by having people dedicated to the workstream.
Within retailers with successful data monetisation strategies, we're increasingly seeing Heads of Marketing Strategy or Heads of Monetisation being appointed to lead the initiatives. Whatever their title, to drive a successful strategy you need someone in charge who is less focused on getting product to shelf and more aligned with innovative revenue streams.
Once your monetisation strategy has been defined, it's crucial this is led by the head of buying or category management and executed by every category buying and management team. It's here that the day-to-day working relationships with CPGs will be formed, shared work plans created, KPIs for success defined and the insight to activation executed.
You may also need to look at your skillset within data management. Customer data is much more sophisticated than sales data. Your staff may not have the skills right now – but upskilling them will help you cut through the noise in the data and ensure the right insights are used.
4.Technology
Assessing your organisation's technology against a few key questions will decide whether you are better off bringing in an external specialist:
- Have I made the right investments, in CRM or loyalty programmes, to generate the data I'm going to need? Am I therefore collecting the right data?
- Am I managing the data I've collected effectively by storing it centrally and enabling analysis and other value-add insights?
- Is my business able to access the data and output of analysis, and use it to make better business decisions?
If you're not confident that your in-house technology meets these criteria, outsourcing to a specialist can save you considerable time and money. That way, you'll also benefit from the best-in-class tools.
When you're building a monetisation strategy and assessing your capabilities against these four pillars, it's crucial you keep your CPGs in mind. How will you embed them into the process? Which insight solutions will you make available to them? And what decisions would you like your CPGs to be involved with?
Having a clear understanding of who your customers are and how they behave doesn't just support better in-store execution of category and promotional workstreams. With this knowledge, you'll be able to activate more relevant, personalised and timely media, both in-store and online, to support your new in-store execution. This means your customers will experience more personalised, relevant offers, your CPGs will benefit from highly targeted, clearly measured campaigns and you'll benefit from the category sales uplift generated from a seamless coordinated multi-channel campaign.
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Examining Share of Visits in the Convenience Store Channel: the Functional Versus the Emotional Shop
October 26 2020
This guest blog was authored by Brian Czarny, Chief Marketing Officer of Factual, a leader in location data.
This year, we assisted dunnhumby with their 2019 dunnhumby Retailer Preference Index: Convenience Store Edition by providing high-quality location data to help with market analysis. Capturing real-world visits is one of the most important retail KPIs today, as channel and media fragmentation is elevating competitive pressures and making it increasingly difficult for brick-and-mortar retailers to grow or even maintain visits. By delving into the data we provided, dunnhumby was able to compare Share of Visits between convenience stores that ranked in the top quartiles and those that ranked in the bottom. Ultimately, they were able to determine that Share of Visits does not differ much across the top two and bottom two quartiles of stores. In fact, they were the same at 14.4%. With the initial results in hand, the RPI analysts wondered: Why was there so little difference between the quartiles, given that almost every other performance measure favored the top performers?
Although Share of Visits data doesn't necessarily provide definitive answers on why the quartiles are so similar, the analysts hypothesized that the Convenience channel has a dual nature and preference patterns are split across emotional and functional drivers. While dunnhumby had previously found that in the Grocery channel, what people think and feel aligns nicely with what they do and how they shop, Convenience proved to be different. It is less clear why some Convenience retailers capture visits through a connection with the customer while other retailers mainly attract functional shoppers and quick trips with their numerous locations. In other words, emotion wins the day for some, but true convenience wins for others -- the sheer number of stores can be effective at capturing trips for gas, a cup of coffee, or getting milk for your morning cereal.
After comparing Share of Visits to other attributes, analysts concluded that there was no correlation between Share of Visits and Assortment, Store Experience, Ready-to-Eat, Private Brands, or Price. However, all stages of the Marketing Funnel and conversion rates were significantly correlated with Share of Visits, which further highlights the importance of location data in measuring and forecasting performance.
These location-based findings supports dunnhumby's initial hypothesis that shoppers do not need to love their retailer to pay it a visit. But it does raise a question: if the retailers who have more of an emotional connection with their customers continue to grow their footprint, will there be increasing pressure on the more functional retailers? To find out, he analysts grouped regional Convenience retailers into two buckets -- More Convenient and Less Convenient -- and analyzed whether either group had a higher Share of Visits. It turned out that there was a statistically significant difference. The Convenient group saw a 15.6% mean Share of Visits while the Less Convenient group saw a 12.7% mean. This is simply association and not causation, but it does suggest that as regional retailers expand and increase their geographical footprints, they could put pressure on the larger incumbents.
If simply having convenient locations becomes less of an advantage for larger retailers, then emotional connection will begin to play a larger role in determining customer preference. In fact, dunnhumby is beginning to see this happen as smaller retailers continue to expand, winning both the emotional and financial battle. As the market and consumer preference evolves, retailers big and small will have to stay on top of the game and leverage the highest-quality data and technology to help them better understand, reach, and engage their customers.
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With vast amounts of data now being generated by every business process and customer touch point, companies in almost every industry are focussed on exploiting data for competitive advantage. This has led to data science becoming a 'must have' capability, and data science teams being rapidly formed in businesses of all sizes, in all sectors.
Having spent nearly 20 years working in, setting up or running teams designed to leverage this competitive advantage, I wanted to share my observations on what it takes to build a great data science team. The starting point is a simple 8-step framework that ensures you begin with the best foundation for success.
Step 1 – Recruit a diverse set of skills
We all know that the first step to building a team is to hire some people, but what skillsets are required to build a high-performing data science team? It's not just about recruiting a bunch of bright PhD students. Make sure you hire people who can understand your business, construct a problem statement and turn analytics into insights. These traits are as important as being able to use mathematical models to create the next algorithm.
Step 2 – Generate insights in an agile way
Analysts and data scientists don't always like agile. They like logical flows, assembling all data before building features and before building models. But businesses often don't have the luxury of time for this approach, wanting to see results quickly as they make day-to-day decisions. You need to strike a balance, be flexible, responsive and adaptable by working in an agile way, adding more data and features as you progress, and building confidence early.
Step 3 – Drive accountability through measurement
It's a tricky thing to do without results to benchmark, but you must estimate the value that your scientific models will add to the business if implemented. Even before you start, you should use your business knowledge to make assumptions about the outcomes. After implementation, measure the value and communicate this to stakeholders. We're all impatient to move onto the next thing, but the best ammunition for arguing for more resource, budget or time is demonstrating the value that your data science team can deliver.
Step 4 – Define the strategy
Be clear on your strategy from the get-go to ensure you don't become order takers for the business on tactical initiatives. Be proactive about where you believe data and models can drive an improvement. Mix quick wins with longer term development to ensure the business doesn't get bored waiting for results.
Step 5 – Integrate into the business
Don't sit in a fancy office in a city centre location because you think it's the only way to attract data scientists. Integrate your team into the business, build commercial understanding by being as close to the other departments as possible.
Step 6 – Communicate your results as well as your existence
Make sure the business knows you are there, what your remit is, and how it will benefit the business overall. Infiltrate as many parts of the organisation as you can and share insights widely, encouraging re-use. Communicate as widely and regularly as you can, demonstrating how and where data science is improving business processes, growing sales, helping win new customers, creating efficiencies.
Step 7 – Influence by building trust
It's natural that people will be sceptical of your team in the beginning, as many decisions are made on experience and gut instincts, not founded in data. Start small to build trust with your stakeholders, find those that are more open to the data-driven approach, and use your results in these areas to influence more widely.
Step 8 – Reuse and build on the best
Build a knowledge bank that ensures that insights and science can be researched and reused. Encourage teams to start with what is already known and develop a champion / challenger approach to model building. Bring the outside in, encourage curiosity and learn from others, both within the business and the wider data science community.
Conclusion
With data scientist now feted as one of the most sought-after roles in business, and investment in building this capability being ramped up across the board, it's clear that if your business is not already making moves in this direction, there's a danger you'll be left trailing your competitors. But do it well, and do it right, and you'll set your fledgling data science team up for the best possible success.
Want to leverage real value from your data asset? We can help - click here to find out more.
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Upcoming Webinar | Insights from the 2021 dunnhumby Retailer Preference Index for U.S. Grocery
January 14 2021
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.
Register now
Retail leaders must objectively understand how their business currently considers Customers before trying to set a more Customer-centric direction and focus. There are some formal assessment methodologies, like dunnhumby's Retail Preference Index (RPI) and Customer Centricity Assessment (CCA), which offer detailed evaluations of a business' capabilities, strengths and weaknesses based on Customer perceptions (RPI) or global best practices (CCA).
The approach outlined below is not intended to replace these formal tools; rather, these observations are intended as a kind of 'toe in the water' to help retail leaders form early hypotheses and points of views. These are rules of thumb, heuristics culled from global experience. Later, leaders might use these observations to informally check progress from time to time as a way of assessing whether the "program in the stores matches the program in our heads".
Hence, the context and laboratory for these suggestions is the retail store, where the rubber meets the road, so to speak.
1. Who really runs the store?
Walking around a store (or better, walking around several), can give many clues toward understanding a retailer's attitude about its Customers, as well as revealing some of the challenges ahead for installing Customer First. As Customers ourselves, we are qualified to assess an organization's 'readiness' for Customer First, simply starting by walking around.
How a Customer experiences the store shapes their perception of the brand, and there are dozens (even hundreds) of 'moments of truth' for Customers in each shopping trip – opportunities for the retailer to win more loyalty, or indeed to lose it. And it only takes one 'bad' experience to erase all the good.
Leaders can form an opinion about the Customers' true shopping experience by observing 'Who really runs the store?' – a way to put on a Customer lens to assess if the Customer, the retailer, the supplier, or no one is driving shopping experience decisions, like range and presentation. For example:
- Choose three sections across the store (telling categories include yogurt, pasta sauces, milk, and packaged lunch meats). Look to see how the product is organized and presented (remember to try to see through the eyes of a Customer).
- Is the section organized by brand (e.g. all Danone yogurt is merchandised together in a recognizable Danone brand block)?
- By Customer benefit or usage (e.g. all brands of probiotic yogurt are merchandised together, as are all Greek style yogurts, all kid's yogurts, etc)?
- Or, by some hybrid but logical planogram rather random plan, with little recognizable logic at all?
- Would you conclude that the product display / layout logic is influenced more by supply chain, by brands, or by the Customer need states or trip missions?
- How broad is the range (e.g., number of varieties or sizes)? How deep (e.g., number of brands of the same flavor or variety)? Does the breadth and depth feel Customer friendly, or confusing?
Of course, analysing any available loyalty data will later tell us how Customers shop the category and that might well be by brand (or flavour or size, etc., and will certainly vary by section). But this first assessment helps us begin to form our perspective on how tuned-in the business is around its Customers, and about where within the business leaders might need to begin to install insights and the Customer language.
2. What messages are Customers receiving?
Store signage not only delivers a written message, but also a type of 'body language' that Customers tune in to, albeit not always consciously. Look around the store to see both the written and hidden messages, and hear the tone being communicated: ask, do messages speak respectfully to Customers? For example:
- Signage at the entrance rudely telling Customers what the rules are, even though 99.999% of Customers will never even think of shopping without shirts or shoes, or wearing roller blades
- Narrow limits on the quantities of promoted products or services.
- Rules and restrictions, terms and conditions.
- Aggressive security barriers and gates at entrances – although sometimes operationally necessary, these also tell honest Customers that they, the shoppers, are not to be trusted.
- Phony expiration dates for promoted prices – Customers learn that the deal will be repeated soon, if not immediately. Best example is the many carbonated soft drink promotions below shelf price that are repeated frequently, and the innumerable 'roller' prices practiced by many retailers.
- Stupid pricing signs (any stupid sign, really).
3. What messages are Employees receiving?
While walking the store, traveling through stock rooms and the employee break room, note the signage and messaging aimed at staff. What seems to be valued more – numbers or people?
What policies and rules guide employee behaviour?
How are they expected to interact with Customers?
Are the messages respectful of staff? Of Customers?
What do signs say about the culture around Customers?
4. Who has the power to satisfy Customers?
dunnhumby's Loyalty Drivers analysis suggests that Customers exhibit four 'mindsets' in their shopping journey – Discover, Shop, Buy, and Reflect. One element of the 'Reflect' mind-set includes the decision to return, exchange, or to request a refund when the product or service does not quite suit.
On your store walk, observe who has the power to satisfy Customers making a return or wanting a refund: is the front-line employee empowered to satisfy the Customer, or must the Manager be called? Is there one 'service' desk where Customers must queue to get their money back, or can the helpful cashier make it good on the spot?
Examine the return policy to assess its sensibility and ease from a Customer viewpoint. For example, must a Customer act within 7 or 30 days, and is a receipt required and signature under penalty of perjury? Is the taking of an oath necessary, or perhaps a drop of blood? The store's practice says volumes about who deserves trust in the eyes of the business. Requiring levels of approvals and higher management involvement (or some other form of hoop-jumping) is neither trusting of employees nor Customers.
The return / refund policies and practices are strong indicators of a company's readiness for, or progress along the Customer-centric journey. Customer First organizations give front-line employees broader authority to resolve Customer needs, and extend the power to satisfy Customers to most members of staff, in some form. For best practices in this area, please see the policies from Nordstrom in the U.S. and Ritz-Carlton globally.
5. Do the words of your leaders matter?
Senior leaders set the tone for how Customers are regarded and treated in the business both by their words and their actions, of course. And the C.E.O.S – Customers, Employees, Owners, and Suppliers – all take notice. It's widely documented that leaders who walk the walk are more effective than those who only talk the talk.
One simple yet powerful way to assess readiness and progress is seeing how leadership's walk and talk align. A word cloud, like the one illustrated below, makes the point very clear. In this example, recent shareholder statements (same quarter) were compared for two companies on a Customer-centric journey. We can see different progress in a form of 'walking the walk' at Retailer X and Retailer Y. The C.E.O.S are hearing what really matters to the leaders, and are forming the Customer culture accordingly, all the way down to store level.
Implications for retail leaders
The store shapes Customers' perception of the brand; there are hundreds of opportunities for the retailer to win or lose loyalty in each shopping trip. Customers take clues, consciously and unconsciously, throughout their entire shopping experience, and draw conclusions about retailer warmth and attitude toward shoppers. And it only takes one disappointing experience to erase all the good.
Retail leaders must take an objective assessment of the shopping experience using a Customer lens to understand their current state and readiness for customer centricity. Pay close attention to the body language and tone of your policies. Store signage, employee empowerment and communications, and practices around assortment and presentation are clear indicators of the organization's attitude about the Customer.
Who actually runs your store?
This is the first in a series of LinkedIn articles from David Ciancio, advocating the voice of the customer in the highly competitive food-retail industry.
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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 david.ciancio@dunnhumby.com
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