Customer Behavioral Analytics in Retail & our Tailor-made Solution

Customer Behavior analytics

What is it?

It is a business analytics solution that helps transform transactional and log data from online and offline platforms into meaningful insights on customer or user behavior. Behavioral analytics is used and applied in a wide range of domains and use cases.

Behavioral Analytics in Retail

These insights would help retail businesses understand customer behaviors and patterns. With the help of advanced analytics and BI solutions, a business can understand the preferences and interests of its customers and optimize revenue by aligning operations, assets, and products. Use cases would include some risk analytics and threat protection as well, however, we would limit this discussion to key use cases such as revenue optimization and operational improvement.

Retail Solutions and Approach

Online platforms depend heavily on the use of website visit tracking and logging tools that provide out-of-the-box analytics and visualization to analyze customer behavior. Tools such as Google Analytics and Adobe Analytics (popularly known as Omniture Site Catalyst) are popular in the industry at present. Typical use cases would be A/B testing and understanding the effectiveness of a page or the impact of an enhancement on a web page, navigation or buying patterns, and more.

In the offline mode (places such as stores, malls, and airports), behavioral analytics in the traditional world were heavily dependent on in-store transactions and then a few offline surveys. With the advent of technology, we now have many offline solutions such as IoT, video analytics, WiFi traffic, and more options to understand customer demographics and behavior. By using modern stacks and solutions such as cloud computing, IoT, and video analytics, the data volume growth is now exponential. There is huge potential to uncover the gaps between growth and opportunity. There are several out-of-the-box solutions available on the market for providing behavioral analytics solutions in offline mode.

Why do we need a custom BI and analytics solution?

Custom BI and data analytics solutions are more helpful when organizations are scaling at an exponential rate. Custom BI solutions would help business owners and analysts arrive at the KPIs and metrics that are not available in the out-of-the-box solutions. For instance, if you want to apply a custom calculation that gives the revenue from the last quarter for a selected product group along with a few business rules or If we wish to extend our existing transactional and logging systems for a behavioral analytics solution, we can consider building a custom behavioral data analytics and BI solution.

BI solutions help users interact with dashboards using drill-down, slice, and dice features. We can arrive at answers to our questions quickly with a few clicks as if we were talking to the data. There are BI solutions that support advanced visualization, as well as AI solutions built in for extracting facts from images (Computer Vision) and text (NLP). The built-in Q&A services in BI Tools allow users to ask questions in natural language.

Our Approach

Our approach would be building a cloud-based data platform using cloud data engineering solutions. Typically we recommend starting small by integrating a raw layer and a curated layer. Business users would start using the enriched dataset using self-service tools. Analytics layer and visualization layers for advanced analytics use cases can be prioritized and built later on the roadmap.

    Recommended stack for an AWS-based data platform: Lake formation, Glue, EMR Athena, Sagemaker, AWS IoT, and a few other services for workload management, data ops, data security, and governance.

    Typical measures and KPIs involved

    Visitor count, dwell time (session duration for online), and sales volume are the key metrics. Other metrics derived from visitor count include conversion rate and dropout rate by page or category, as well as a few additional dimensions captured along with the visits. A few popular KPIs include visits by brand, Average dwell time by brands & stores, top-selling brands, low-performing brands, and stores, visits by location, peak days and visitor forecasts, occupancy rates, revenue per square foot, visits by demographics, etc.

    Video Analytics in Behavioral Analytics

    Video analytics plays an important role these days in understanding a wider audience in an offline mode. Key advantages of video analytics are that the coverage would extend beyond the store and extend the visibility of non-transactional customers. For example, you can compare the visitors from transactional volume against the total visitors, which uncovers more visibility on the customer conversions and patterns. Video analytics solutions at present are more sophisticated and accurate in detecting demographics (age and gender), object detection, identification and tracking, and finding repeat customers. We can also arrive at the mood of the customers while entering or exiting the store.

    Use Cases and Benefits

    Retail can benefit from behavioral analytics in many areas, including sales, marketing, operations, and inventory. Below are a few examples of the key benefits of a behavioral analytics solution.

    • Understanding the performance of products and the effect of seasonality
    • Forecasting and maintaining optimized inventory levels and staffing
    • Understanding the buying patterns
    • Measure the performance of a page online or the placement of a product in-store; optimize page layouts online (A/B testing); and optimize store layout in an offline environment.
    • Understanding target customer segments and improving marketing abilities
    • Direct sales personnel to the appropriate location.
    • Product recommendations to increase conversions
    • Increase order conversion rate by optimizing and improving the user experience of navigation and process flow.

    Challenges

    • Privacy and compliance issues need to be addressed while using video analytics or other advanced solutions involving sensitive customer data (PII). 
    • Ensuring the right solution and having the ability to translate the ground truth into actionable insights requires engineers with good programming skills and problem-solving abilities.
    • Arriving at an accurate ROI of the solution requires good synergy between the technology, marketing, and business teams.

    Need Help?

    Techmango has built several BI and data analytics solutions for our customers in retail and other domains. Reach out to us if you need more help assessing whether a BI solution is right for your use case or not. We can assist you in assessing, estimating, and building the solution. We have full life cycle experience in delivering data and analytics solutions using a wide range of data analytics (cloud and on-premises) and leading BI solutions (Power BI, Tableau, QlikSense, etc.). 

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