An Insider’s Guide to Retail Data

In the current climate, brands and retailers need to remain one step ahead of the game to ensure that they stay competitive in an already oversaturated market. To do this, they have to consistently practise streamlining and optimising their processes to make sure they make the right data-driven decisions for their business. 

From running lucrative offers and promotions to deciphering how much stock to push to the shop floor, every action has a consequence. Every action can either help to drive the business closer to success, or push it further towards its demise. Recently, WNS conducted a study into data and analytics, reporting that 78% of retailers surveyed are now looking to accelerate their response to market changes, with 70% focusing on improving customer experience and loyalty. Because of this, they noted the need for retailers to leverage their data and analytics capabilities to understand the benefits of analytics-driven decision-making at scale.

Thanks to the rise of big data, brands and retailers are now turning to retail analytics to provide data-driven insights, helping them to inform their future decisions and strategies. Supporting this, IBM recently revealed that 62% of retailers report that the use of information and analytics creates a competitive advantage for their organisation. Not only does data have the power to drive better decision-making, but it can also help them to optimise their operations, enhancing the overall customer experience.

In this blog, we’ll delve into the world of retail analytics tools, explore the roles of retail analysts, and demonstrate how data can significantly improve your retail processes. Also, if you’ve not yet been acquainted, we’ll introduce you to Reapp, a premier retail data tool designed to elevate your retail strategies.

Exploring the World of Retail Analytics

In order to delve into the world of retail analytics, we must first understand the process of gathering, analysing, and interpreting data related to retail operations. This data itself may come from various sources, including sales transactions, customer feedback, social media interactions, and inventory levels. By analysing this data, retailers can gain actionable insights that inform their current and future business strategies, enhance customer satisfaction, and increase sales.

Additionally, analytics also help retailers make better decisions about which promotions to run and which marketing strategies to focus on, especially when it comes to things like customer loyalty schemes and how to promote NDPs. 

What Does a Retail Analyst Do?

In order to help retailers access and understand their data, they may deploy the use of a retail analyst or a retail software toolkit, allowing them to obtain insights from their data that can help them to make informed decisions. 

The steps an analyst or analyst software may follow are:

• Data Collection: This is the process of gathering data from various sources, such as POS systems, customer surveys, and online transactions. It’s important to note that retailers should aim to collect and analyse various data sources to gain a deeper understanding of their business. For instance, a brand could look at the connection between consumer shopper analytics with product attributes. This approach may help them to optimise their store layouts to convert shoppers into buyers. 
• Data Cleaning: This step ensures that your data is accurate, consistent, and free of errors. It also means that circumstances of duplicate data or any missing data fields can be avoided.
• Data Analysis: This next step will involve the use of statistical tools and software to help understand the data to identify trends, patterns, and anomalies.
• Reporting: Now that we have the vital information, detailed reports and dashboards can be created to present data insights in an easy-to-understand format.
• Strategy Development: This phase involves collaborating with other departments to develop strategies based on data insights to improve business performance.

When data is used correctly, retailers can thrive…

Luckily, our Reapp platform can make the art of integrating data analytics a breese. At its core, Reapp is a suite of intelligent analysis software products and tools designed to help businesses score sales and better manage their stock. 

Through the Reapp Insight platform, brands can create quick and easy automated reports made directly from fresh data, helping them to craft actionable insights that not only revolutionise – but reward – users. Additionally, the Reapp Rewards and Loyalty platform leverages the use of customer data to help brands get closer to their customers by building the perfect loyalty program and capturing first party data.

How Can Retail Data Improve Your Brand?

Did you know that there are four main types of data obtained in the retail sector that can help businesses to understand their customers, the products they stock, and the effect of key drivers? 

There four actionable data types include:

• Customer data: This encompasses behavioural, demographic, location, and typical spending information. It helps retailers to build a customer profile and can help them to understand which products are in demand. This also allows them to reduce waste and avoid loss.
• Product data: This data shows which products are performing well and which are not. It can help retailers to understand current demand and supply.
• Inventory data: It is important for brands to see their ingoings’ and outgoings’. Without sufficient inventory data, meeting customer needs becomes difficult. It aids in forecasting market demand and supply.
• Sales data: This data reveals market trends and helps retailers understand which products are selling during economic changes, such as the cost of living crisis. This allows them to adjust product supply and manage their costs effectively.

Now that we’ve identified the types of data out there, we can explore the benefits of using this information to help retailers achieve excellence.

Improving the Customer Experience

With the data that brands obtain to help them understand customer behaviour, they can start to deliver the very best customer experience:

Personalising Marketing Efforts: Data can reveal individual customer preferences and their typical buying habits, which means that retailers can tailor their field marketing strategies to ensure that they are successful. This reduces the likelihood of retailers losing money which could be used for other pressing business matters. 

Examples of retailers utilising data to personalise their strategies includes Tesco with their Clubcard Challenges and retailer Boots. Last year, they partnered with Channel 4 to help advertisers hone their content by merging its Advantage Card customer data with Channel 4’s VOD platform. 

Enhance Customer Service: Thanks to the data that qualitative customer feedback can provide, retailers will have the ability to identify common pain points and address them promptly to improve customer satisfaction.

Optimise Store Layouts: By using foot traffic data, retailers can design store layouts that enhance the shopping journey, whilst also ensuring the likelihood they cross paths with selected in-store promotions and offers.

Push Your Inventory and Price Optimisation to the Max

It is essential for brands and retailers to keep their inventory management in check. Using data, they can prevent overproduction, reduce waste, and ensure adequate stock levels during high demand by predicting demand accurately. Additionally, brand price optimisation is critical for maintaining profitability and meeting customer demand. Brands can use historical sales data and market trends to set competitive prices that maximise profit margins.

When it comes to products and their brand relationships, retailers can also use data to improve their supplier relationships. Data can provide insights which can analyse supplier performance to negotiate better terms and improve supply chain efficiency.

One retailer that does this successfully is Ocado, who leverage the use of data to optimise their supply chain. The company predicts demand, reduces waste, and aims to maximise the availability of fresh groceries through their Ocado Smart Platform (OSP), which harnesses the power of artificial intelligence.

Predict Market Shifts Before They Happen

Staying ahead of market trends is crucial for maintaining a competitive edge. Using predictive analytics, brands will have the ability to anticipate changes in customer demand and adjust their inventory accordingly. They will also have the ability to identify emerging trends using market data to capitalise on them before their competitors.

A great example of a brand utilising data to stay ahead is alcoholic beverage brand Diageo, who recently unveiled their ‘Flavour Forecast’. It was created in collaboration with AI Palette, an AI and machine learning tool that identified emerging trends across the food and beverage industry by tracking global conversations on online and social media platforms. By doing this, they increased customer satisfaction by creating products that the consumers actually want to see. 

Additionally, brands can use data to identify potential risks and develop strategies to mitigate them before they impact the business.

The Four Types of Retail Analytics

Retail analytics can be categorised into four main types, each serving a unique purpose:

• Descriptive Analytics: Provides insights into past performance by analysing historical data – e.g. popular products, peak sales periods, and customer preferences. It answers the question, “What has happened before?”
• Diagnostic Analytics: Explores the reasons behind past performance by identifying patterns and correlations. It answers the question, “Why did it happen?”. This could relate to consumer shifts due to events like the cost of living crisis.
• Predictive Analytics: Uses statistical models and machine learning algorithms to forecast future trends. It answers the question, “What is likely to happen?”
• Prescriptive Analytics: Provides recommendations for actions based on predictive insights. It answers the question, “What should we do?” This is useful for brands who are concerned with their future performance.

For retailers to grow, they will need to ensure that they are including all four forms of retail analytics to improve decision-making and develop effective retailing strategies.

Introducing Reapp: The Perfect Retail Data Tool

Reapp is a comprehensive retail data tool designed to help modern brands and retailers harness the power of data analytics. 

Here’s what makes Reapp the perfect choice for your retail business:

• Advanced Analytics Capabilities: Reapp offers robust analytics features that cover all four types of retail analytics, helping you understand past performance, diagnose issues, predict future trends, and prescribe actions.
• User-Friendly Interface: Reapp’s intuitive interface makes it easy for users at all levels to access and interpret data insights.
• Real-Time Data: Access real-time retail data insights to make timely decisions and stay ahead of the competition.
• Customisable Dashboards: Create personalised dashboards that highlight the most important metrics for your business.
• Comprehensive Reporting: Never manually pull a report again – Have the latest retailer data at your fingertips and see unmatched time savings in no time.

Boost Your Retail Data Game Today

In conclusion, retail data analytics are an indispensable tool for any brand looking to thrive in today’s competitive market. By leveraging the power of data, brands and retailers can enhance the customer experience, optimise inventory and pricing strategies, and stay ahead of market trends. In the future, we predict the use of retail analytics will become much more seamless – we predict that it will be integrated into the everyday process of brands. We’re looking forward to seeing where the world of retail data will take us in the months and years to come! 

It’s clear that the benefits of data can be pivotal, which is why it’s important to invest in the right retail analytics tools. Here at Tactical Solutions, we’re proud to be experts in the retail data field. Our unmatched data analytics services are complemented by our proven track record in helping brands and retailers to drive impressive results for their businesses. You can trust us to provide you with the tools you need to unlock the full potential of your data.

Don’t wait to harness the power of retail data. Boost your retail data game today with us and start making data-driven decisions that propel your brand to new heights in no time.