Forget what you heard in science – it’s data insights that make the world go round.
Although brick and mortar stores might not appear to rely on numbers and digits in the same way online retailers do, they are still crucial parts of a well-oiled machine.
You see, it can be easy to think that the retail industry is strictly driven by stand-out marketing and customer service. However, these can be fuelled by clever data collection and analysis – producing jaw-dropping actionable insights that fuel great decisions, sending you and your strategies through the roof.
Think Willy Wonka’s Great Glass Elevator. Without the property damage.
In this guide, we’ll touch on how you can use the latest in data insight technology to boost customer experiences and brand recognition in stores nationwide – using it to create successful field marketing choices that get stock off the shelves and past the scanners.
We’ll also talk about:
- What data insights actually are
- How we can delve deeper into what’s happening shelf-side
- The key benefits of data insights
- Which types of data makes marketing magic happen
- And finally, how Reapp can help you make the most of your existing data
Listen. Guesswork is hard work.
But with Reapp, we can help you build key customer relationships, bolster new and exciting marketing campaigns and see which products are flying (or flagging) at the touch of a button.
Long gone are the days of trialling and testing. Our suite of data-led software creates in-depth reports at the click of a button, offering brands complete visibility into what’s happening on the shelf and beyond – all in one place.
Our data provides real-life insights that are easily understood and can be used to investigate compliance in stores, monitor field marketing activity, and identify factors that may be affecting product sales.
Even better, we can offer tailored reports and bespoke dashboards to give you a crystal-clear view of your products in stores up and down the country.
It’s data-driven science that makes sense.
But let’s get into the nitty gritty, shall we?
What are data analytics, then?
In a nutshell, retail analytics involves the collection, collation and digestion of large amounts of data. This can then be used to enhance pricing strategies, streamline supply chain operations, and improve overall customer satisfaction; data analytics in retail enables companies to create customer recommendations based on their purchase history, resulting in personalised shopping experiences and improved customer service.
Large data sets are useful for predicting trends and informing strategic decisions through market analysis.
The Importance of Data-Informed Decisions in Retail
Utilising data that can help you make clearer decisions can help brands and retailers alike to obtain real-time insights and calculate predictions – all to ultimately improve performance. Through this, brands can test the success of different strategies and make informed business decisions for sustainable growth, using accurate data taken directly from store-floor sources.
You see, data is a huge part of what makes good decisions, well, good.
Let’s have a closer look at the reasons why.
Continual growth
The most important factor of data when it comes to making salient decisions is its ability to stoke growth while preserving consistency overall. That’s because data-driven decision making allows brands and retailers alike to look closer at vital insights, collated from a wide number of functions, operations, and even separate departmental activities.
With over 3 billion units at your fingertips with Reapp, actionable insights and benchmarks can help you consistently make smart choices from shop floor to management suite. This results in continued growth and profitability, thanks to accurate sources and quick-on-the-draw report generation.
And who doesn’t love speedy sales?
Innovation, innovation, innovation
Using data-driven decisions can absolutely determine whether your business sinks or swims in a hyper-saturated retail market. This, combined with the rapid rise of technological influence on our marketing strategies goes to show that electric strategies are powered by data-fueled visualisations, with proven success.
MIT Sloan School of Management professors Andrew McAfee and Erik Brynjolfsson performed a study in conjunction with the MIT Center for Digital Business. From this, they learned that among the companies surveyed, the ones that were primarily data driven benefited from 4% higher productivity as well as 6% higher profits. Considering this was eight or so years ago, we can only assume that the margin between this has grown, as retailers that approach information as an investable asset will have more knowledge at their disposal.
From this, multiple departments can access the insights brought on by data, allowing them to innovate separately and collaboratively – producing a stand-out commercial ecosystem powered by little 1s and 0s.
Minding your (new) business
Making decisions based on freshly-squeezed data results in the identification of fresh – and exciting – business prospects. Plus, you can get a comprehensive overview of the main operations of your company by digging deeper into easily available information through the use of a real-time software solution.
From this, you’ll find actionable insights and possibilities to advance your development and create fresh ideas that carve out that essential competitive edge. After all, if you’re armed with deep-dive insights that will enhance your judgement, good decision-making can only serve to advance your business.
It just makes sense, young Padawan.
Adaptable. Reliable. Incredible.
Listen, the digital world is constantly evolving – as is its impact on physical retailers – so in order to keep up, use data to help you make more educated and effective business decisions.
Data can even help you spot new trends and patterns that affect both your internal activities and the industry around you, with analytical tools that let you pivot and change insights in a pinch. From here, you can make judgments that will guarantee you always remain competitive, relevant – and lucrative – if you have a deeper understanding of these trends or patterns.
It’s all about speaking the same language, right?
A Closer Look at Different Data Types for Actionable Insights
Data, data, data.
While it’s billions of units and thousands of rows consisting of ones and zeroes, field marketing teams can collect and analyse a number of different types to aid their efforts.
At a glance, this includes:
- Sales data
- Inventory data
- Customer demographic data
- And much more!
These can be collected from a variety of sources, both online and offline. Whether that’s social media monitoring (where appropriate), surveys, point-of-sale systems, loyalty programs, and even promotions, we can get a top-to-bottom view of what’s happening in any number of your stores.
But how do you analyse this data?
Don’t worry, we’ll delve into the juicy stuff next.
Gaining deep understanding from analytics solutions
Alright, class is in session.
There are four types of retail analytics that each play a crucial role for retailers when it comes to providing key insights into what’s happening in their shopper’s heads and baskets.
The four different types of data are:
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
Descriptive Analytics in Retail
Descriptive analytics – which is the most popular sort of data analysis – helps retailers make decisions by structuring their data in a way that tells a story. Cool, huh?
By integrating unprocessed data from numerous sources (POS terminals, inventory systems, OMS, ERPs, etc.) – it can produce insightful analyses of past and present performance, creating a real-time, real-handy way to see where you were and how things are in the heat of the present (marketing) moment.
Descriptive analytics, to put it simply, uses data to explain “what” is moving and shaking on your shelves. However, unless it’s used in conjunction with other types of data analytics that can shed more light on patterns and connections, it can’t always address the “why.”
Diagnostic Analytics in Retail
As the simplest type of “advanced” analytics, diagnostic analytics is all about the “why” of certain retailer problems.
Diagnostic analytics employs statistical analysis, algorithms – and occasionally machine learning – to go deeper into the data and discover correlations between data points, using the same raw code as descriptive analytics.
However, anomalies can be identified and possible issues can be flagged using diagnostic analytics: that’s if results do not match pre-programmed benchmarks and rules, of course.
In the past, only the most skilled analysts carried out all of this manually. In order to do this, they would sort through data, use statistical models, search for trends, and discover correlations.
However, that takes heaps of time, so we can now use brain-boggling algorithms and reporting techniques to help us sift through the numbers and find the problems in record time.
Predictive Analytics in Retail
Effective predictive analytics uses a mix of findings from both descriptive and diagnostic analytics to forecast the future. Spooky.
It harnesses algorithms and statistical methods to detect clusters and exceptions, enabling the prediction of future trends, which is helpful for any business worth their salt when it comes to tough decisions. But to do this, retail predictive analytics must leverage AI, advanced mathematics, and intelligent automation to ensure accurate forecasting – otherwise it’s just making stabs in the dark.
Luckily, predictive analytics automatically detects clusters and exceptions. Which is clever stuff, really.
Prescriptive Analytics in Retail
Say ‘aaah’, as prescriptive analytics are at the final frontier of analytics – meaning it’s the most advanced.
That’s because prescriptive analytics can tell retailers “what you should do next” to get the best results – making it an integral part of anyone’s data-led tool box.
But to make clever recommendations, a prescriptive analytics system needs to not only know what is likely to happen in the future – but also understand which actions will lead to the best possible result.
It’s scary stuff. But it’s incredibly important if you want to stand out from the crowd.
The benefits of using analytics tools in your retail strategy
So now you know how we do it – I guess the next big question is: “how does all this number crunching actually help me make decisions – and why’s this so beneficial?”
Enhances customer experience
Firstly, data analytics help retailers get the full picture of how their customers shop. They can then go away and use this data to cook up a seamless customer experience, taking them from product selection to scanning – with a focus on personalisation and ease-of-use for each and every person who enters the shop.
From ensuring inventory is never low on stock or ensuring that planograms are being adhered to (got to keep those products within arm’s reach), data analysis can help you see what’s working and what really isn’t.
And as we all know, happy people make for majorly loyal customers.
Trend setters and predictors
Big brands often have a sale during major holidays or to make the most out of existing stock. But do they pull this out of thin air? No! That’s because they have plenty of data on hand to quantify these ‘sales experiments,’ which goes hand in hand with tricks of the trade, such as ‘sentiment analysis’, to see if your customers would be receptive.
For instance, marketers are aware that customers tend to buy the most throughout the festive seasons. Armed with this knowledge, complex machine learning algorithms are deployed to establish the context, with any information gleaned from data points then used to forecast the best-selling products in a particular category.
It’s a rather clever mix of prescriptive and predictive analytics.
Keeping an eye on ROI
Data analytics helps brands and retailers accurately spot high ROI prospects. Retailers, for instance, can use predictive analysis to assess how their customers react to certain marketing initiatives and determine how willing they are to make a purchase.
This can serve as a handy (and accurate) compass when it comes to new and exciting campaigns in the future.
Old-fashioned customer retention
A good customer is one that always comes back. Much like a boomerang with a debit card.
However, upset and unhappy customers are enough to cause lines on the forehead of any retailer worth their salt – especially since they are hard enough to win back.
It doesn’t take a boombox and a declaration of love, however. You can use data analysis to spot where a customer might have ‘dropped’ a product in your sales pipeline, or determine which products are starting to go stale on the shelf.
When we begin to spot issues ‘in the wild’, your marketing team can then swoop in with a number of prepared incentives, such as promotional material, discounts or even loyalty points to bring them back – which are all excellent choices.
Who said numbers couldn’t be romantic?
New locations, new scopes
Looking to set up shop in a new spot?
Retailers can use data to help them discern the best areas where their target audience spends plenty of time. Analytics also offer data on:
- market circumstances
- demographics
- consumer spending power
These are all factors that make it easier for retailers to decide where their products will do well, while attracting new footfall and stoking a reliable customer base – wherever they go.
Big decisions made easy with Reapp
By using our incredible suite of field marketing software and real-time, real-accurate reports, you can make game-changing decisions with the click of a button.
From understanding, predicting and actioning how products are used in-store, we give retailers the power to make incredible improvements through informed decisions.
With Reapp, we analyse information from various points in the retail environment and incorporate it into our cutting-edge analytics tools to produce reports that quickly and easily visualise what’s going on in-store. We’re pretty hefty too, with the brain-power to tackle whole ranges or hone-in and spot-check specific lines or wastage in a few simple clicks.
From EPOS to product range availability and visibility, store compliance to shelf share, we go above and beyond to deliver real outcomes from exceptional data points.
Want to see how we can help? Get in touch for a free demo today to Reapp the benefits.
