One of the most well known examples of how Big Data can drive sales is that of Amazon. They have perfected the analysis of all their data in order to increase their sales. But also smaller companies as well as offline companies can use Big Data to drive their sales to the next level.One of the most well known examples of how Big Data can drive sales is that of Amazon. They have perfected the analysis of all their data in order to increase their sales. But also smaller companies as well as offline companies can use Big Data to drive their sales to the next level. It is all about knowing which data you already collect, which data you require and how to combine the different data sets to gain insights required to increase your sales. Whether you do B2B sales, B2C or even enable C2C sales, Big Data can help to increase your conversion.In the old days, there was a in-balance between the seller and the buyer, where the sales agent often had a lot more information at hand than the buyer. With B2C, but also more and more for B2B sales, this has changed drastically. Customers can scan a barcode or perform a simple search query to find similar products at different website for different prices. The balance has changed in favour of the buyer. Customers use the data to find the right product at the right price. Organisations can, however, do the same to increase their sales. Knowing when the competitor adjusts prices can be valuable information and an (automatic) adjustment in price and/or service could result in not losing the sale.
In a world where customers have more information at hand than sellers, sales agents should not rely on gut feeling. Too often, especially in B2B sales, gut feeling is an important part of the negotiation strategy of the sales agent. Based on the relationship with the customer and the experience of the sales manager a price is determined. According to an article by Joe Boissy, Chief Marketing Officer Vendavo, on SalesandMarketing.com, predictions based on “gut feel” are only about 40% of the time correct.
As is for customers, more information is better, and sales people need to have the right information at hand to counter negotiation tactics used by the buyers. Ideally they need to have this information in real-time at their fingertips; who is the customer, what are the interactions, transaction history etc., which is important information to determine the sales price. Fortunately, with the every expanding amount of data, this becomes a lot easier for organisations. Big Data can really take your sales to the next level:
Finding new markets and leads
Analysing your website statistics and social media can help your organisation identify the products and services that are regularly viewed, but not as often bought. Traditional website analytics already provide a lot of information for companies, but being able to link that data to social data will help you understand barriers standing in the way of a purchase.
Analysing the social data of your customers or your target group using sentiment analytics and natural language processing, will provide you with valuable information about what people think of your products and/or services. Who are they and what are they, and their social networks, looking for? This could help you identify new markets, new target groups and therefore give you new leads.
Driving Repeat Sales
Data from social networks can also be used in order to drive repeat sales. Knowing your customer is the start in increasing repeat sales. When you start combining transactional data with social data and all customer touch points within your organisation, you are generating a true 360-degrees customer profile. This will help you better understand your customer and what they are looking for. Based on such valuable insights you can offer the right product to the right customer at the right moment, without annoying the customer. Especially when you combine it with recommendation engines, such as Amazon is doing really well, you provide a valuable service to your customer that will result in increased repeat sales.
Reduced prospect research time
The best sales professionals understand that in order to win the customer, it is important to know as much as possible about them. According to a survey performed by CSO Insights, sales representatives are, often manually, analysing 15 different external sources like Twitter, LinkedIn, Facebook and the web, next to all the internal data sources they have to analyse. According to a different study by Aberdeen, sales representative spend 24% of their time doing research, resulting in lost sales opportunities. Big Data can do all this work for the sales representative and deliver automatically generated, detailed reports of prospects so that all your sales reps have the same information, in a fraction of the time. In addition, Big Data analytics can find the common traits among the best customers to determine new customers or better approach existing customers.
Predict future sales
Analysing sales data from local stores across the globe can help organisations accurately select the best selling products at product and/or store level. This information will help organisations determine which products to sell at what location and to make real-time adjustments if necessary. This will ensure for example that a store is not out-of-stock of a certain product when the product suddenly goes viral in a certain area, as Big Data analytics could have predicted it.
Big Data and Sales is big and more and more startups are entering the enterprise market of improving sales using Big Data Analytics. The latest company to receive a $100 million funding on a $ 1 billion valuation is InsideSales.com, a Big Data Startup that sits between marketing automation services and giant CRM vendors like Salesforce. Its objective is to connect the different services in order to help sales teams work better. Other companies in this area are Velocify, that helps sales teams optimize their sales process among others and Five9, a company that has several tools to increase conversion rates and improve sales performance.
Many organisations are already using Big Data analytics to optimize their sales organisation. One of them is Intel, which developed a predictive analytics solution to identify and prioritize which resellers have the greatest potential for high-volume sales. With this new solution, Intel’s sales organisation now analyses data in real time from various sources to determine the potential for each customer. T-Mobile USA managed to reduce their churn by 50% thanks to Big Data and of course Walmart is relying extremely heavily on Big Data to increase their sales by creating the Social Genome, a vast, constantly changing, up-to-date knowledge base, with hundreds of millions of entities and relationships, of their customers in order to recommend the right product at the right moment to the right customer.
Big Data offers many different possibilities for your sales organisation and if implemented correctly, the right Big Data Strategy can significantly improve your sales.