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in-store analytics

In-store Analytics: 5 Major Challenges Retail Companies Face

The competitive retail landscape has increased the need for customer analysis across different retail segments. This has resulted in the growth of demand for in-store analytics. Today companies in the retail sector have started implementing in-store analytics to understand customer behavior and retain existing customers. Consequently, in-store analytics has become an integral part of a conventional retail store. In-store analytics can help retail businesses to make informed decisions and gauge their performance in real-time. Also, it can help them in offering better and personalized customer experience.

In-store analytics is the key to bolster customer experience and deepen consumer privacy in the retail sector,” says a retail analytics expert from Quantzig.

However, due to the immense scope of in-store analytics, there are significant challenges that retail and CPG companies have to deal with to derive desired business outcomes. In this article, our team of analytics experts have highlighted a few challenges to assist retail companies to stay ahead of the curve.

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IN-STORE ANALYTICS CHALLENGESIn-store Analytics Challenges

Collecting data from disparate sources

Data is generally generated in different format from various sources within an organization. . For retail companies, it is quite challenging to collect data from disparate sources and unify these data into a single platform. As a result, companies face hurdles in analyzing the pool of data they collect.

Accuracy of the data collected

Accuracy of data is one of the major factors responsible for accurate analysis. To make in-store analytics solutions work exactly according to the business requirement, companies need to ensure that the right quality of the data is collected. This can help them maximize category growth and with the help of in-store analytics. Also, without accurate data, analyzing heat map is difficult for companies making them unable to gauge the impact of their store layout on return on sales (ROS).

Talk to our analytics experts and learn how we can help you analyze your in-store traffic patterns and offer behavioral insights to improve business outcomes.

Ensuring data security and compliance

With the constant rise in data breaches, retail companies need to ensure the security and compliance of the data collected. For successful implementation of in-store analytics solutions, companies need to carry out penetration tests and internal security audits to secure the data.

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Extracting the valuable insights from the data

In-store analytics solutions can help companies in the retail sector to extract, transform and load the data efficiently to reveal customer buying patterns and market trends. But for this to work successfully, companies need to ensure that they can extract valuable insights from the data collected. Also, companies in the retail sector need to assemble specific data insights and look for correlations to derive the best business outcomes.

Learn more about in-store analytics solutions and its benefits

point of sale

Point of Sale Data Analysis: 3 Best Practices for Retail Businesses to Succeed

In this digital era, the retail industry has been evolving rapidly. The in-store experience has gone far beyond conducting a simple transaction at the point of sale (POS). The functionality of point of sale has enhanced recently and more developments are on the horizon. Today’s digitally empowered customers are expecting better service and experience in real-time. Real-time engagement technologies, such as the Internet, kiosks, digital signage, even mobile apps, are revamping retail and putting consumers in control of the shopping experience. In response, companies that want to conduct business in this next generation of retail are learning to position their point of sale systems at the center of this Internet-oriented shopping experience. This is the reason why point of sale data analysis has become very important for retail companies. With the help of point of sale data analysis, retailers can deliver good customer experience at store levels. In this article, we have curated a list of a few best practices that can help retailers to establish a clear foundation for their point of sale data analysis strategy and remain flexible enough to adopt new solutions as they emerge.

Our data scientists can help you optimize your store layout, improve merchandising, enhance promotional offers, predict staff scheduling requirements, and measure customer waiting time. Get in touch with them right away.

 POS DATA ANALYSIS

Point of Sale Data Analysis Best Practices

Best Practice #1: Analyze the trend data first

To improve their point of sale data analysis strategy, retailers need to monitor the market trend data timely through effective corporate reports and scorecards. They need to look at both shorter- and longer-term market trends to obtain desired business outcomes. Shorter-term trends can proactively help in fixing issues before they extend into longer-term trends.

Quantzig’s advanced storefront layout analytics solutions help retailers to build a store layout that drives an increase in traffic, average transaction value, and maximize conversions. Request a FREE proposal to gain in-depth insights into our portfolio of analytics solutions.

Best Practice #3: Conduct distribution analysis

Tracking new items can be done easily and accurately by creating a report that tracks the percentage of stores selling an item. Here, the distribution would only be recognized once the first sale is recorded. Distribution analysis helps in measuring the percentage of stores that carry the particular item. Also, this analysis can help in understanding how quickly the product is getting through the supply chain – from the warehouse to the store’s receiving, then out from the back room and onto the shelf. As a result, retail companies can make changes to their point of sale data analysis strategy and maximize their profit.

To learn more about how our storefront layout analytics solutions can help you improve customer-centric floor plans and enhance merchandising operations, request for more information below.

Best Practice #2: Determine stocking schedules at store level

For retail companies measuring out of stock (OOS) lost sales are probably one of the most challenging tasks. But to improve point of sale data analysis, they need to monitor hourly sales data with significant gaps as this could be a strong indicator of OOS issues. If you are only looking at average units per day, you would not see a difference between weekday and weekend sales. Therefore, it is important to look at sales per hour as it helps to identify an OOS issue during what should be a peak time for sales.

By leveraging our point of sale data analysis solutions, you can gain a holistic view of POS transactions and ROS while continuously monitoring end-to-end transactions from payment source to payment completion. Request a FREE demo to know more.

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A Beginner’s Guide to In-Store Analytics

The rapidly-growing, competitive retail landscape has increased the need for customer analysis across different business segments, especially e-commerce. This is the reason why the demand for in-store analytics has gone off the roof. Today conventional retail businesses have started implementing in-store analytics aggressively to retain their customers. Due to this factor, in-store analytics is now n integral part of conventional physical stores.

At Quantzig, we understand the importance of in-store analytics in retail business. And to help companies in the retail sector to excel in the competitive landscape and stay ahead of the curve, our team of experts has curated a detailed guide to in-store analytics. This guide can assist companies to improve profitability and retain their customers significantly.

Are you finding it difficult to track all the cart and basket values in your store? In-store analytics may hold the key to success. Get in touch with our experts to know how our analytics solutions can help your retail business.

What is in-store analytics?

In-store analytics is the process of collection of customer data and applying them to operations of the retail store. This can offer actionable insights into their business on both macro and micro levels. Is it sounding too complex? But it is not, provided you have proper retail analytics solutions in place. A proper analytics dashboard offers data-driven insights that make all data easily understandable and quickly applicable. In-store analytics solutions provide pre-built reports that help retail business in identifying key metrics responsible for retail performance. Furthermore, this helps in decision making and devising an overall business strategy that is based on data-driven facts and not on assumptions.

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What is in-store analytics important for retailers?

#1: Facilitates better pricing decisions

In-store analytics has the potential to analyze price sensitivity efficiently. It can offer better visibility to retailers into the factors responsible for fluctuations in price. Also, it helps in identifying the points that have a major impact on the volume of sales. Furthermore, this can help in generating additional revenue for the retail business and safeguard them from any future price fluctuations.

#2: Track conversion rates

In-store analytics plays a crucial role in helping retail businesses to make informed decisions by keeping track of factors leading to conversions which is the heart of retail analytics. Also, these insights assist in monitoring retail performance, understanding consumer behavior, and enhancing the shopping environment. Furthermore, advanced analysis combined with data obtained from all these sources enables retailers to improve marketing operations, drive sales and boost the productivity of retail staff.

Reliable data leads to smarter decisions. Our retail analytics solutions help companies to understand customers and their behavior. Based on our analytics solution businesses can obtain profound insights into the buying process of customers and their journey. The results, in turn, can help businesses to drive customer traffic, monitor customer journeys, and translate prospects into loyal customers. Request a FREE proposal to know more about our portfolio of services.

#3: Understand customer behavior

In-store analytics helps in understanding the behavior of customers. This can further help businesses to send targeted offers and content depending on the response of a customer towards the brand. Marketing operations become more efficient if marketing is done through a targeted approach. This has high chances of inducing sales and thereby, converting a prospective buyer to a loyal customer. 

Our retail analytics guide is here to help you improve sales and achieve higher profits. Download the free supplement now.

Benefits of In-Store Analytics

Benefit #1: Improves the shopping experience

Today customers are well informed, and they research a lot before making any purchase. A retail business if incorporate in-store analytics to their marketing operations, can identify buying patterns of customers and their buying preferences. Consequently, this can help in enhancing the marketing strategy and improving the shopping experience of customers.

Benefit #2: Enhances customer support service

If you are into retail business and want to improve your customer service, the most important way to do that is gaining insights into customer’s response towards your brand. Conducting surveys help but it is not the proper solution because sometimes the customer’s response is not genuine. Therefore, tracking and analyzing customer data can help more in improving customer service and in-store analytics makes this very easy.

Our in-store analytics solutions can help you see how the customer flow translates into conversion. Request a FREE demo to gain better insights.

Benefit #3: Prevents theft and burglary

For retail stores, shoplifting is one of the most regular problems that they face. In-store analytics can come to the rescue here. By leveraging in-store analytics, retail stores can identify the spots that are highly vulnerable to shoplifting. Also, the data from the in-store analytics dashboard can help retail stores to strategize their marketing operations and take key decisions in improving security at the store. Consequently, this can help in dealing with theft and burglary.

Benefit #4: Optimizes store performance through real-time dashboards

In-store analytics dashboards offer specific insights to examine the product placement in the store and the optimal floor layout. Also, it helps in identifying frequented and non-frequented areas in the store. The in-store analytics dashboard also offers actionable insights into conversion by section and traffic by section. Furthermore, it helps in identifying profit maximizing patterns and paths. 

Want to know more about the benefits of in-store analytics and how it can enhance your retail store performance? Request for more info below.

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Why In-store Analytics in Retail is the Key to Make Your Bricks Click

For brick and mortar retailers, this is no easy time. The boom in online retail has left the sales of physical stores at a standstill.  The market space which is becoming increasingly digital is compelling retailers to turn towards advanced analytics techniques to ensure that their business survives the competition. Moreover, juggling between offering customers the right products at the right prices along with an exceptional customer experience can seem to be a daunting task for retailers. Adopting in store analytics could be the answer for companies in the retail industry to overcome this hurdle.

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What is in store analytics?

In-store analytics in retail provides meaningful insights from customer behavioral data. Retailers leverage several techniques such as the use of smart carts with location beacons, pin-sized cameras installed near shelves, or the store’s Wi-Fi network to identify the number of shoppers entering the store, their movement inside the store, and the key areas/aisles that they visited. This can even be used to extract basic demographic data, such as gender and age group. In store analytics can connect the dots between consumer, retail store, and buying decisions based on the data collected.

Why is in store analytics in retail important?

Competing with online stores is no cakewalk for brick and mortar retailers. Ergo, it is imperative for them to collect as much data possible about their customers and their buying behavior. In store analytics in retail gives businesses clear-cut solutions to the following conundrums:

Pricing decisions

Pricing is one of the trickiest tasks for retailers. Most retail companies invest in resources that churn out tons of in-depth data on sales and pricing. Out of this, only a few succeed in turning this data into actionable insights. Retailers often end up making knee-jerk reactions that could have adverse effects on their business. For instance, in the case of an increase in production cost, they tend to raise the prices in direct proportion to the manufacturing overheads without understanding its impact on sales volumes. In store analytics helps retailers perform a price sensitivity analysis, which gives a better visibility about when and by how much should prices go up or down. This can generate additional revenue for the retail company and safeguard them from price hikes by the competitors.CTA QZ

Understand consumer behavior

Customer behavior is highly dynamic and often hard to track. In store analytics provides retailers with a better understanding of the customer behavior. A form of in store analytics in retail called the mood analytics uses CCTV camera images to monitor the facial expressions of a person. This can help retailers send targeted content and offer them in store depending on how a customer is feeling. For instance, if the mood analytics reveals that the customer is confused about making a purchase from a particular category, then the retailer can promptly send an offer message to the customer’s mobile that is valid if the purchase is made within a particular time frame, say one hour.

Visual merchandising

Visual merchandising is key for retail companies to attract customers’ attention. But how would they decipher what would work for their business and what wouldn’t? In store analytics can offer real-time data on the effect of visual merchandising on the customers in the store. This can help retailers to experiment with different visual merchandising techniques and eliminate the ones that do not bear fruit.


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Why Is ‘in-store’ Analytics Key to Unlocking the Retail Industry’s Potential

The rising pressure from online players is forcing brick and mortar companies to rope in the most innovative technologies into business and invest in various in store marketing strategies and campaigns to attract customers to walk into their stores. However, unless the effectiveness of these techniques is measured, the effort goes in vain. But the big question for retailers is how can they measure the extent to which their strategies are successful? The answer is through in store analytics. Companies in the retail industry can leverage in store analytics to measure and analyze in real-time the performance of campaigns and other marketing activities. This helps marketers to improve their decision-making capabilities and optimize performance. Though a business’s ability to benefit from such analytics depends heavily on the environment where it is deployed, the possibilities of in store analytics are countless in any environment from shopping malls to individual stores. Also, the benefits of in store analytics are not immediately visible; they can only be reaped over time. But, the results attained are totally worth the wait. Let us explore some of the key benefits that retail industry players can gain by employing in store analytics into prFree demoactice:

Real-time measurement of store performance

It is essential for retailers to have a clear understanding of the customer’s behavior before undertaking marketing and promotional campaigns. In store analytics provides players in the retail industry with the tools that would help them gain real-time actionable insight into the customer behavior. This would help them to measure the effectiveness of previous strategies and structurally plan new campaigns that influence the buyers. For example, retailers can measure how a change in window displays affect the capture rate from passersby to store visitors.

Optimize layouts and categories

In the store, analytics gives brick and mortar companies deep insights on the buyer behavior and customer shopping patterns. These insights open up countless possibilities for companies in the retail industry for optimizing in store operations, such as store locations and store layout.

Enhance shopping experience

In the online scenario, the use of A/B testing to better understand the customers’ buying behavior is one of the best practices. When it comes to brick and mortar model, businesses can devise in store analytics to learn from their previous actions and perfect their operations over time to provide an optimal customer experience.

Increase marketing ROI

An investment becomes worthwhile only if the company can maximize their return on investment (ROI). An efficient in store analysis allows marketers to choose the campaigns and strategies that would yield the maximum returns. For example, by analyzing the sales funnel, marketers can focus on the best opportunities that bring the highest marketing ROI.

 Accurate performance measurement

As mentioned earlier, in store analytics gives retailers the idea of which strategies are best suited for their business. With this, they can further benchmark and set the standards for performance. Benchmarking helps companies to measure the positive and negative deviations and accurately state the reasons for the same.


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