Big Data Analytics to supercharge Sales !!

In the post-recession slow growth world, profitability is back on the agenda. 

Customers have more information at hand than sellers; organization should not rely on gut feeling to sell. Sales agents often spend much time on the prospects who are not likely to buy or who won’t buy enough products. 

What they need is to have the real time information at their fingertips of who is the customer, what are their intentions, interactions, transaction history to make a profitable impact at the first moment of truth.

With today’s advances in every field of life, most of our interactions as customers or vendors get recorded through digital world and we create humongous data points. The data that is generated in this fashion is massive in volume, comes from multiple sources and in multiple formats such as audios, videos, chats, text messages, picture files, system logs, social media posts like tweets, fb posts etc.

Current CRM or database systems are not designed to take this huge amount of data, of variety of formats and process it to show trends and establish correlations, efficiently.

Big Data has emerged to handle such demands and have been greatly responsible of many success stories at large organizations such as Google, Cisco, MetLife, Wal-Mart, Salesforce.com, Forbes etc.

We all know the great example of Amazon Cross-Sell using Big data of massive click streams and historical purchasing data from over 150+ million customer accounts, tie that up with over 1.5 billion items in their retail catalog and more than 200 fulfillment centers around the world to produce an improved world class recommendation engine for personalized sale to each customer.

Intel on the other hand developed a big data analytics predictive engine to identify which re-sellers have greatest potential for high volume sales.

Wal-Mart is using Big data to increase their sales by creating Social Genome to reach customers or friends of customers by analyzing their social footprints.

Salesforce had acquired ExactTarget to make every customer interaction a personalized relationship.

CustomerMatrix is helping organizations by collecting all the structured and unstructured data available there combined with prescriptive analytics to create action alerts to increase revenues.

Infer combined internal company data with external data such as employee count, social presence, job openings, company size etc and built personalized predictive models to score each lead to convert to have most revenue impact.

Retailers are using customer’s smartphone signals and in-house surveillance camera video streams to see where customer go in their stores, which products they look at, to design better product placements and encourage customers to stay longer and buy products.

It will more prudent to use Big data analytics to increase sales by gathering customer feedback even before the sale.  By following the customer on his/her 3 stage decision making journey from trigger (compel him to look for the solution to his problem), research (become as knowledgeable about customer’s problem & solutions as possible) & purchase (make an impression on customer as thought leader & trusted advisor to his problem) stage, sales teams can supercharge the sell.

How Marketers can benefit from Big data Analytics !

Internet explosion has enabled organizations to go closer to their customers & do a super personalized communication. 

People now spend more time on the internet than any other form of entertainment.  The demand for internet capable devices like smartphones, tablets have increased exponentially.  Most of the people are buying products online or compare products online.

Customers spend hours on the internet and leave behind millions of tweets, posts, likes, links, images, videos, chats, comments, surveys, blogs.

Businesses need to use this all big data forms to get a 360 view of the customer for marketing.

• Behavioral data that has orders, transactions, and other customer activity as recorded by the business
• Interaction data including email, chat transcripts, self-declared information, and records of calls between the business and customers and web click streams.
• Attitudinal data including opinions, preferences, needs, and desires. These are often discovered through survey responses or social media data.
• Financial data that is present in the company’s internal systems such as sales, revenues, profits.

This big data can make a substantial impact to:

• Increase Customer retention and loyalty - helps you discover what influences customer loyalty and why they keep coming back again and again.
• Improve Customer engagement - Helps you understand who your customers are, where they are, what they want, how they want to be contacted and when.
• Marketing optimization – helps you determine the optimal marketing spend across multiple channels

Let us see some examples of how Big data is making an impact on Marketing for cross-sell &up-sell.

You are familiar with both cross-selling and up-selling if you’ve ever visited a fast-food restaurant like McDonald. “Would you like fries with that?” is an example of cross-selling. “Would you like to super-size your order?” is up-selling.

Almax has created "smart mannequins" that have cameras for eyes and analyze shoppers' faces to detect age, gender, ethnicity, and a variety of other characteristics.

Sony mixed modern big data, social media analytics, and old-school marketing such as direct mail email marketing — and generated 300% more sales than control groups. They used their customer database & found out their strong social networks, influencers. A campaign was targeted to these influencers which is termed as viral marketing.

eBay is using “my Feed” so they can follow categories of items for newest listings.

Netflix is using real-time processing for digital marketing to its customers.

Walmart created WalmarLabs, created a search engine to understand what someone is searching for and goes through millions of tweets, Facebook’s likes, blog posts and more to detect purchase intent and boost sales.

Tripadvisor is using clickstream analysis to analyze what more than 56 million monthly visitors want and make them happy.

Visualize the scenario where you walk into your favorite apparel store like Gap or Target. Surveillance cameras mounted on the door immediately detect who you are and instantly beam identifying information to the in-store sales associates. An app on the sales associate's iPad then correlates all of your shopping characteristics such as loyalty, past purchases, cross-channel preferences, service incidents, and social media footprint and provides your consolidated view. With this information, a sales associate walks up to you as you are entering the store, greets you by name, and inquires about your most recent purchase. This level of personalized attention dramatically alters an individual's in-store shopping experience…and it's not that far-fetched…………

Internet of Things & Big data Analytics

We have entered the Digital Enterprise era.  All the businesses are aiming at reaching their Customers anywhere, anytime, any platform with any device.  All such smart devices or physical objects that are connected to the internet & are continuously emitting data and communicating with each other is called the Internet of Things (IoT).

You will find all these objects around you in your day. Your Fitbit wristband is monitoring your sleep, waking you up at the desired time, tracks your activity. When you go out for walking or jogging in the morning, your Nike shoes with built-in-sensor are collecting all the data and track your time, distance, pace & calories burned. 

All this humongous data is an ideal candidate for Bigdata Analytics. Let us see how does 3 V’s of Big data come into this scenario. All the data which is generated by these devices or things is voluminous or recurring at specific intervals.  This streaming data is “always in motion” so there is a velocity.  The variety is coming from all different sensors sending data.

Big Data will help make companies smarter, more progressive and give them a business advantage. You can have better control over your business with IoT through better tracking and better reporting. Let us see some examples.

Sigalert.com provides sensor-based analysis of traffic on highways.  This when combined with Waze, a world's largest community-based traffic and navigation app, helping drivers avoid the frustration of sitting in traffic, cluing them into a police trap or cutting 5 minutes off of their regular commute by showing them new routes they never even knew about. 

Great River Medical Center is one healthcare organization that's connecting many of its medical devices into a network using Microsoft's Windows Embedded, thereby enhancing the patient care by speeding delivery of medications, reducing an average 1.5 hour wait time, down to just 30 minutes. Getting the correct medication to patients faster has improved patient outcomes and reduced the rate of readmission.

With the Loxone iPhone app, you can access, monitor and control your home from anywhere.

A food distribution company can use sensors in trucks that send temperatures, humidity; point to point travel times back to the data center for further analysis.

Today's tech-savvy consumers have the option to shop whenever and wherever they want, including on mobile devices.

Retailers have a lot of use of IoT & Big data. They can measure the real-time customer traffic in & out of the store with video cameras, current queue lengths, historical transaction data & footfall data to predict how many more checkouts to be opened. This helps improve the customer experience.

Utility companies have installed smart meters to monitor energy, water & gas consumption.

Airbus A380 has sensors that monitor the wear and tear of the flight in real time which helps in the preventive maintenance of parts before they fail, reduce the warranty costs and increase operational efficiency.

As IoT becomes mainstream, it can play a big role in areas such as supply chain management. When customers' preferences or needs can be tracked in real time, businesses have the opportunity to react accordingly and immediately, with options such as dynamic messaging, pricing, or service delivery.