Power of Big Data: Sales

In the first part of the series "Power of Big Data", I wrote about how Big Data can influence the development of marketing activities and how it can help make the right decisions related to promotion (you can read the first part of the series here: Power of Big Data: Marketing). If the first part was about Big Data for marketing, it makes perfect sense  that the second part should be Sales - these two area are often inseparable. When we think about Big Data for Sales tools, it most often concerns e-commerce companies, because they very often use tools for real-time data gathering and analysis (more about Big Data for E-commerce). However, it should be made clear that e-commerce is not the only beneficiary of data management tools because every organization related to sales can benefit from the analysis and use of its data in order to optimize their sales funnels. 

In this short article, I will try to list the benefits that those can bring to a sales pipeline, and how Big Data can increase sales. Properly implemented and used tools can become an excellent source for creating data-driven approaches to the sales strategy - and, as I wrote in previously mentioned texts, data analytics and management tools are the future of e-business. Below, we will look at the general possibilities of the above-mentioned implementations of data handling tools - we will not focus on the technical aspects of implementing individual solutions. Each of them should be adapted to the specifics of the organization that will use it, a tailor-made solution that will perform its task best, based on the uniqueness of the company's situation

Data in sales.

Let's be honest, the amount of data that can be generated by a properly designed sales funnel is huge, and the mere handling of it can be difficult if we do not have the tools prepared for it. However, not only the amount of data is important here, but also their complexity.  The amount of data is not only increasing but they are more and more precise. Not so long ago, the very fact that we could recognize where the user, who made a purchase on our site, came from was a great help in creating a sales funnel. And of course, it still is. Now, however, there is much more data. We know not only where the user came from, but we know his behavior, we know what products he saw before he chose the one who bought it. We know - if he has not made a purchase - where he has abandoned the cart (abandonment rate) and whether it has returned to it (e.g. thanks to real-time marketing). And we can know much more! The world of data gives us enormous possibilities, thanks to which we can predict the purchasing decisions of potential customers and thus influence them. Of course, without their recognition and use, we can also lose these customers to companies that, thanks to the analysis of behavior, will make it easier for them to go through the sales path.

The data that we can obtain regarding customer behavior may be a key element of sales, and thus the existence of an organization that is focused on it. However, both their number and complexity elude the traditional methods of analysis - for this you need professional Big Data tools, solutions created exactly for the needs of the organization. 

Big Data data for sales

Can Big Data increase sales? Or, because it seems to be the better question, how to use Big Data to increase sales. Below, we present a few general possibilities, thanks to which sales processes can be improved and thus bring better results than before:

1. 360 view of the customer behavior - We talked about it before, in the Big Data for Marketing post, but this time we will focus not on how they react to marketing messages, but on what behaviors they show when they are already in the sales funnel (at every level!). This knowledge will prove to be irreplaceable when optimizing the funnel - and when taking advantage of other opportunities that Big Data gives to sales.
2. Geoanalytics sales strategies - Imagine the data that helps you see where your products sell best and which are less interesting for your customers. And we are not talking here only about defining countries or cities - thanks to comprehensive data, we will be able to distinguish much more optimized groups, for example people with a given education, living in the suburbs of a given city, working at given hours.
3. Optimization of cross-selling strategies  (e.g. with Complex Events Processing) - cross-selling is a sales optimization technique to maximize profits from a single sale. Thanks to the available tools and Machine Learning operations, the algorithms will be able to better select additional products offered to customers, and thus increase the likelihood of a purchase (next best offer).
4. Pricing optimization - thanks to the data analysis, the organization will be able to propose to the given customers the most potentially interesting (from their point of view) discounts and promotions. Moreover, it will be able to predict which user will be interested in a given product and thus present him with the best option. A great way to gain customer loyalty - to offer them what they really need. Another dimension of optimizing the price is actually optimizing the revenue, so taking into consideration not only propensity to buy but also the supply chain costs to calculate the promotion.
5. Customer journey - why did the customer leave the cart? Why, despite browsing products or services, he did not decide to buy? Thanks to data analysis (also in real time), we will be able to answer this question and eliminate errors, as well as improve the customer's path to facilitate the purchase. In today's world, time is a currency, and hardly anyone will want to waste it on a tiring sales process.
6. Predict Future Sales - Thanks to complex event processing tools, it will be possible to predict the demand for products that are still sprouting, and to prepare an offer for potential customers on time. Knowing what's going to be hot in a moment will help you prepare your marketing and sales campaigns to leave the competition behind. 

Using Big Data tools for sales optimization

Optimizing sales processes is something that every organization should strive for. Meeting the needs of customers will ensure their greater interest and loyalty. Automation of sales processes will increase profits and avoid turmoil in the sales funnel. Real-time data analytics will prevent abuses and frauds, as well as inform about potential technical problems.  Event processing will help understand their decisions and prepare offers directly to their needs. There are many possibilities offered by Big Data solutions.

Of course, each of the points indicated above could be developed and used-cases prepared, because the Big Data possibilities for sales are huge, and it is difficult to fit them into one article. It serves to raise awareness of how dependent we - or our organizations - are becoming on the flow, analysis and management of data. With a huge amount of products and competition, and more and more diversified customer groups, it will be difficult to do without these tools.