As organizations have developed the capacity to gain greater insight into customer behavior, it is essential to use innovative analytics practices to succeed. For large and small retailers, it is essential to be able to not only react to, but also accurately predict the trends and nuances in the market.

The Big Data & Analytics for Retail Summit (June 19 & 20, 2014) was organized by the Innovation Enterprise at Chicago.  Illustrated intermittently with case studies, interactive panel sessions and deep-dive discussions, this summit offered solutions and insight from the leaders operating in the Big Data space.

We provide here a summary of selected talks along with the key takeaways.

Highlights from Day 1.

Here are highlights from Day 2 (Friday, June 20, 2014):

Rafael Alcaraz, Vice President, Global Advanced Analytics, Digital Media and Strategic Foresight, The Hershey Company explained the role of location intelligence in marketing analytics during his talk "Location Intelligence: The Missing Component in Retail’s Use of Data Analytics". Location intelligence brings the "Where" factor to performance analysis and enables a deeper analysis of business information; all designed to assist companies in reaching conclusions and making the next, best business decision.  He outlined the applications of location intelligence to improve data analytics.

By harnessing information already within Business Intelligence (BI), Customer Relationship Management (CRM), Supply Chain Management (SCM), and other enterprise applications, location intelligence enables companies to integrate location dimensions with performance management, reporting, predictive analytics and campaign management solutions to increase sales and optimize marketing operations. Location Intelligence assists companies in making complex location-dependent business decisions by representing and displaying business intelligence data on maps to identify hidden trends, customer relationships and behaviors, as well as enable a deeper marketing analysis.

Consumer's purchase decisions today are being influenced by a wide variety of factors, which makes marketing extremely difficult and complex. Even though marketers need to study a lot of factors such as Price, Weather, Distribution, Promoted Volume, Radio, TV, Print, Seasonality, and Macro Trends; in order to succeed they must have a simple view of the world through conceptual frameworks to decompose the effects. It is easy to study these factors separately, however, in real life, they all act simultaneously. Decoding this simultaneous effect is critical to better understand how any investment to drive sales is actually performing. Understanding the full picture is vital to have an insights driven supply chain.

Shoppers have many choices. Sale occurs only at the conjunction of availability, right relevant message and value proposition. All consumer interactions are important. Thus, they must be measured and included in the Analytics for marketing decisions. Location intelligence empowers retailers to optimize Site Selection and Store Performance.

Jason Raguso, Vice President, Gongos gave an interesting talk on "Architecting an Intelligent Organization". Getting the right information to the right person in the right way to make the right decision. Seems logical, right?  But “insight logistics” is much easier in theory than it is in practice. In adopting the technologies to accommodate new forms of data and analytics, we’ve unconsciously skipped over foundational elements required to make analysis meaningful for decision-makers.

Through simple examples, Jason illustrated the imperatives for architecting today’s intelligent organisation and the cultural nuances to make it relevant. An intelligent organization is one that is able to successfully implement the right balance between Performance (quickness & accuracy) and Innovation (learning & experimentation).

In order to succeed, business managers need to think about:

• How do I drive service? [Rethink your sandboxes]
• How do I instill ownership? [Invest time and money]
• How do I ensure scalability? [Channel your schizophrenia]
• How do I promote collaboration? [Create a Jedi Council]

 
Companies need to be very careful while making business decision such as whether to build or buy analytics solutions, and whether to build their data architecture as centralized or decentralized. He concluded his talk with the following quote:

"We cannot solve problems by using the same kind of thinking we used when we created them." - Albert Einstein

Mark Carlock, Multi Channel Retailing Analytics & Optimization Lead, Clarks delivered an informative talk on "Content, Context, Community, and Clarks". With the emergence of Omni Channel it is more and more imperative that data is distributed and consumed correctly. With so many moving parts to the puzzle a business must be ready to adapt and be ready for when the next challenge arrives.  Adapting an agile approach to reporting and to the use of data, Clarks is smartly using web analytics to shape the future of the Business and the Brand.

Mark revised the Analytics at Clarks, driving it towards understandable, actionable analytics through rigorous A/B testing, continuous measurement of not just conversions but the entire consumer experience. He stressed on the need of simple pilot tests, intuitive visualization and getting business buy-in.

Based on his experience, he strongly recommended the marketers to focus on Content, Context, and Community.

Murtaza Lukmani, Associate Director, Insights & Analytics, MediaComgave an insightful talk on "Advanced Text Mining of Online Product Reviews for Better Visibility of Merchandise Focused Customer Sentiments". All online retailers gather valuable information from their customers in the form of Product Reviews online. This information is collected using review form on the website and through post purchase survey emails which are sent to the customers. We can leverage this data to improve the product selection process and improve the overall merchandise quality. However majority of the data is in unstructured text format, which is fundamentally different from quantitative score data. We need to perform advanced text mining to derive these sentimental insights.

Through a live example, Murtaza demonstrated how online retailers can harvest this qualitative information. His team created a sophisticated methodology to measure customer sentiments across a retailer's product assortment, in order to inform the business: what was going wrong! They categorized product reviews across parameters such as Fit, Delivery, Durability, Price and General Comments. Text mining was done using RapidMiner and text string clusters were created for deeper analysis.

Sentiment trending across top categories helped pin point why certain categories were losing revenue share over the years. The overall category sentiment score cards helped rate merchandising effectiveness. Besides, sentiment mining was also used to learn the language customers were using to describe their sentiments. The sentiment describing keywords were then used to describe products in all outbound marketing communications. This helped with building customer relevance in messaging and brand damage controls when needed.

Related:

• Big Data & Analytics for Retail Summit 2014 Chicago: Day 1
• Big Data Strategy: Datafication
• Interview: Thomas Levi, POF on How Online Dating is Improving Matching through Big Data