Empowered consumers and shoppers are the results of constant technological disruptions, and they have their expectations from their favorite brand or a retail outlet selling their favorite brand.
Retailers need to make sure that their empowered customers get convenient, satisfying, and exceptional experiences throughout their interactions with them. Ask yourself this very crucial question, “what sets you apart from the crowd?”
If you are doubtful or do not seem to have an answer for that, let me help you out. There has been an unprecedented rise in digital disruption that has been taking place across industries thanks to new digital technologies. If you are not the early adopter of an appropriate technology according to your industry vertical, you will lose the market share to the ones that do.
There has been an unprecedented rise in digital disruption that has been taking place across industries thanks to new digital technologies. If you are not the early adopter of an appropriate technology according to your industry vertical, you will lose the market share to the ones that do.
Business leaders must transform their business, yes, but they need to leap with the help of AI-driven analytics.
This article will delve into the insights data analytics, and AI can provide to retail owners and decision-makers to stay ahead of the curve.
What is retail analytics and why it is important?
As a retailer, what insights do you want for a better and faster decision-making process? AI-powered retail analytics provides insights into –
- Other important retail aspects
Retail data analytics encompasses several separate fields for creating a comprehensive insight into your retail business health and sales. It also gives you details on the areas that require improvement and reinforcement.
Retail analytics help retailers understand consumers shopping behavior, run businesses more efficiently, and deliver improved customer service.
The retail analysis goes beyond trivial data analysis by using data mining and data discovery for aligning disparate datasets for producing actionable business intelligence insights.
For instance, retailers can use their sales data analysis for identifying their ideal customers as per the diverse categories such as age, preferences, buying patterns, purchase location, etc.
How can retailers use data analytics?
Providing an enhanced in-store experience coupled with personalized recommendations, offers, and product support as per age, gender, location, and customer behavior is important to stand out in the crowd. AI and data analytics are useful technologies that provide all these data in an insightful, meaningful, and understandable format to decision-makers.
1. Behavioural Insights
Major challenges that retailers face are:
- Improving the customer conversion rates
- Personalizing their marketing campaigns
- Predicting and countering customer churn
- Lowering the acquisition costs
AI-driven analytics enable retailers to counter these issues by understanding customer shopping behavior. With the ever-increasing consumer interaction points, the data has started becoming diverse and complex at the same time. But with powerful business intelligence tools that utilize the culmination of modern technologies, it gets easier for business owners to derive actionable data after collating and analyzing the data.
2. Enhanced in-store experience
Wherein merchandising has always been associated with aesthetics; there has been a dearth in measuring the impact of merchandising decisions. There is also a new shopping trend where customers shop online after looking over their desired products in-store.
Now that iBeacons and IoT technologies have made their way into the market; retail stores can now analyze their products’ in-store behavior and assess its impact on their developed merchandising efforts. Retail business owners can use a data engineering platform for personalizing their customers in-store experience and drive loyalty by giving offers to customers who frequent the stores regularly. Gaining insights into consumer behaviour can also allow retailers to increase their promotional material effectiveness and boost cross-selling of products and services.
Retailers can gain their customer behavioral insight from
- Web Analytics
- Point-of-sale systems
- Loyalty card data
- Mobile apps
- Supply chain systems
- In-store sensors
- CCTV Cameras
Using the collected data and applying predictive analytics omnichannel retailers can:
- Have a test run of all their marketing and merchandising tactics on customer behaviour and resulting sales.
- Personalize their in-store services by using customers purchase and browsing history for identifying their needs and interests.
- Observe their customers in-store behaviour, analyze, and categorize their customers for creating offers and discounts and even for loyalty points programs.
3. Manage operations and value chains
With faster product life cycles and complex operational chains, retailers need analytics for transforming their supply chains and product distribution channels for cost reduction. For driving their business and gain a competitive edge, retailers need to focus on returns. They can use business intelligence tools for optimizing –asset utilization, cost, performances, and service quality.
For increasing operational efficiency, retailers need a system that can unlock the insights hidden in their logs, sensors, or even the machines. These insights include information that helps retailers:
- Improve decision making
- Enhance operations performance
- Reduce costs
Artificial intelligence can assist retailers in gaining the most influential patterns in their data
- predict sales over a holiday season
- determine how much staff they need for the week
- ensure their inventory matches demand
Some fun details related to AI, predictive analysis in retail
The Artificial Intelligence in Retail Market was valued at USD 1.80 billion in 2020 and is expected to reach USD 10.90 billion by 2026, at a CAGR of 35% over the forecast period 2021 – 2026.
- Product recommendation and planning will be the growing area for AI in the retail sector.
- The advancement in retail data analytics will drive the growing adoption of artificial enabled devices and services.
- A variety of different technologies involved in AI and Big Data, such as machine learning, natural language processing, deep learning, and more will benefit retail industry with automated machine-driven decisions.
- 33% of users are more likely to increase their satisfaction due to the personalized experiences offered by AI – Aberdeen, and IBM
- Companies that have invested in AI are three times more likely to acquire new customers.
- Companies that have adopted AI are 2.5 times more likely to improve customer retention.
Conclusion: AI is enabling retail with data-driven insights
AI has various benefits in the retail industry like cost-saving, increased productivity, faster resolution of business problems, faster delivery of new products and services, increase in innovation which is rapidly making its way into many advanced solutions, including autonomous vehicles, smart bots, advanced predictive analytics, in the retail space. – Consumer Technology Association
A fresh take on online grocery shopping
How we helped one of the largest grocery chains transform the grocery shopping experience?
For every business, delivering the ultimate customer experience is the core foundation. Decision-makers who are tasked with maneuvering their business with a high ROI factor can easily do so with AI, ML, and data analytics by creating a unique customer profile for their user base and execute their strategy accordingly.
Artificial intelligence in culmination with other upcoming technology is playing an essential role in retail operations. AI coupled with machine learning, data analytics, and automation derive better value in terms of time and cost savings. As a retail brand trying to make your mark felt in the market, you must partner with a digital product consultant that has been helping big retail brands in the US since long.
If you want to inculcate new technology into your retail process or want to know details of merging disruptive technology in your business for staying on top of your retail game, then let’s chat about it.
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