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8 Ways Big Data Will Impact Sales in 2017
Blog / Sales Management / Jan 27, 2017 / Posted by Nate Vickery / 19721

8 Ways Big Data Will Impact Sales in 2017

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The fast development of advanced big data technologies has already revolutionized many business fields. Sales and marketing are definitely on the top of this list. The big data technologies help marketing and sales professionals to define product and service prices and manage their sales networks. In this article, we’ve shared some of the ways big data will impact our sales strategies in 2017.

Optimizing pricing strategies

The research conducted by McKensey has discovered that more than 25% of business revenue comes from innovative pricing decisions. Pricing has the potential to drastically improve a company’s revenue. In the future, big data will have a much more important role in the development and implementation of pricing strategies.

Setting the best prices is a major analytic challenge, especially in big companies that sell thousands of products per day. That’s why these companies will need to automate their products and price analysis. Many successful companies like Uber already use big data for shaping their pricing strategies and implementing them in real time.

Greater customer insight

Since sales are one of the most dynamic business fields, sales departments and professionals across the corporate world have quickly adopted the big data technology and all the benefits it provides. In the last couple of years, companies have been trying to develop and implement advanced relationship-driven sales strategies. In the near future, they’ll use big data analytics in order to improve the customer responsiveness in their campaigns and gain a greater customer insight.

Better customer analytics

Accurate customer analytics is one of the most essential factors for the development of a successful sales strategy. In 2017, the role of big data in marketing research will reach new heights. Today, many companies have their own mobile apps, which means that they can generate huge amounts of data from customers’ phones.

Structuring and analyzing these data pools can help companies to improve various aspects of their sales and marketing strategies. By using advanced big data technologies and improving their customer analytics, companies will increase their customer acquisition and the amount of revenue they draw from each purchase.

More efficient product improvement

Although product improvement is not the part of the sales strategy, it drastically affects the company’s sales figures. In the consumerist society, products need to be updated and improved on a regular basis and big data analytics helps corporate designers and engineers to choose which innovations to implement. Big data technologies provide the necessary infrastructure for analyzing product failure patterns and choosing the most important improvements.

Defining customers’ decision journey

Today, consumers use a wide variety of different marketing channels to reach their favorite products and services. The internet allows its users to shop (around) until they drop and that’s why companies need to have a better understanding of their customers’ decision journey. In order to do this, their sales and marketing departments need to follow their customers on and off their website.

This creates tons of data that needs to be structured and analyzed and that’s a job for the company’s data center. The conclusions that can be derived from analyzing customer browsing can help companies to optimize their websites for better conversion and adapt their sales tactics to better match the consumers’ needs. Pipeliner CRM is a perfect tool which can then utilize this data through its lead and customer management features.

Automation of the sales process

Advanced big data technologies can automate the whole sales process and make it more efficient. Recently, many companies have been developing their own model of ‘Algorithmic Marketing’. This is a concept that uses ‘self-learning’ and advanced data analysis to create more relevant customer interactions.

For example, online stores can use this approach to implement the dynamic pricing strategies. They can also give the most relevant product suggestions, by analyzing customers’ behavior, price comparisons, inventory and various other parameters.

Smart email campaigns

The email marketing has become more popular recently. Many companies started sending newsletters with their latest offers. This type of newsletters can only be effective if they’re personalized and relevant. Companies often use big data analysis to analyze visitors’ behavior on their platform and categorize them in accordance with their product preferences. This enables marketers to send highly customized and fully relevant offers to visitors, which can drastically improve the company’s sales.

Improving website navigation

Navigation and browsing experience is the most important characteristics of every online store. They directly influence a company’s sales and direct customers towards the checkout page. Unfortunately, many eCommerce websites have a very bad navigation. This way they are losing a significant percentage of their customers and directing them to their competitors.

In order to improve online store navigation, companies need to analyze customers’ behavioral patterns and determine potential drawbacks and bottlenecks. This will help them to choose the best eCommerce solutions. Since big online stores have millions of visitors, their companies need to use big data analysis for analyzing their behavior on the platform.


World’s data is growing by more than 40% each year. Most companies that implemented different types of digital marketing and sales programs are also facing a huge data pile up. Although some companies find this to be a little bit burdening, top market players see huge data piles as goldmines from which they can draw conclusions that will help them to improve their business practices and speed up their growth.

About Author

Nate Vickery is a business technology expert mostly focused on business automation and efficiency. You can read and learn more of his insights on

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