How to Boost Sales with Data
As margins get tighter and competition increases, enterprises are seeing data as one of their biggest competitive advantages. By finding smarter ways to leverage data and business analytics information from internal and external data sources, businesses can boost sales by optimizing sales processes, better predicting customer behaviors, creating more effective marketing campaigns, and delivering exceptional experiences to customers. The trick is finding the right people and BI analytics capabilities that can help correlate and prioritize information, turning it from raw data into real customer insights that highlight real market opportunities.
These potential gains are part of the reason why researcher IDC predicts a 50% increase in revenues from the sale of big data and business analytics software, hardware, and services between 2015 and 2019. (Source: IDC). Let’s take a closer look at how today’s organizations are boosting sales with smart big data initiatives.
- Optimize sales processes- Business intelligence platforms and business analytics tools that aggregate data quickly and deliver automated reporting with visualization capabilities can help teams better track sales performance. With the ability to see in real-time how actual sales stack up to forecasts, there is greater transparency in the company’s performance overall. Also, individuals have access to actionable intelligence and are in a much better position to adjust and make smarter decisions about meeting targets. Not only that, cloud-based and as-a-service analytics capabilities improve access to that data which means that teams, no matter how big or how small, have all relevant sales and customer information at their fingertips when they make decisions, either on-the-go from a smartphone or in the office.
- Better predict customer behaviors- By collecting data about current customers and combining that data with external data sources, such as sales data from syndicated providers such as Nielsen or IRI, customers can create a clear picture of who’s buying, which products or services are selling and the best ways to connect with those buyers. Customer segmentation, customer match analytics, and third-party data help fill any gaps that may have been left looking solely at historical customer data. Bringing in data from multiple silos helps produce a more accurate and validated ‘buyer profile.’ As a result, the information is more predictive of future customer behaviors and more prescriptive regarding what steps should be taken to increase sales. Organizations can leverage this information to develop new products or services and identify cross-sell or upsell opportunities that will likely have the most significant impact.
- Create tailored and effective marketing campaigns- By leveraging data, companies can also develop more effective and targeted marketing campaigns that will resonate with customers. Knowing details about buyer preferences, shopping habits, past purchases, and overall market trends can shape campaigns. In terms of product and service focus, content and messaging in ads, what marketing tools are used (i.e., emails, ads, direct mail pieces, etc.) as well as placement (i.e., Facebook, Google, mobile options, etc.). Knowing customer contact preferences and when customers are most likely to make a purchase will also help companies prioritize marketing spending to optimize sales and maximize brand engagement.
- Deliver exceptional customer experiences- Using big data and analytics insights strategically way can also help companies deliver the best customer experience possible, regardless of what channels are used. For example, if a customer searches for a company’s website and lands on specific pages, the business can utilize these details to get that person in touch with the most useful service agent possible. If that customer clicks on a ‘learn more’ website link, calls in to speak with an agent or chats with customer service online, that data is recorded and correlated with other customer history information. It can be accessed to see what that individual was looking for and help determine how to provide the best possible experience.
- Real-time offers to improve engagement- Companies can take customer experiences to the next level by leveraging data in real-time to deliver timely, high-value offers that are in sync with customers’ social and mobile preferences, product searching habits and location. An example of this is ads that appear in the popular community-based traffic and navigation app Waze. When users search for a local pizza shop near them, ads for nearby Papa John’s or Domino’s locations also pop up as an option for the searcher. Similarly, Starbucks may send targeted, time-specific offers to customers based on locations where they placed and picked up mobile orders using the company’s app. In that same way, a search for Hulu may also bring up offers for new Amazon Prime members. Using real-time data about customers can ensure that customers have the best possible opportunity to connect with the brand.
More and more leading companies are turning to data and BI analytics to improve customer relationships, build brand engagement and convert more sales leads. Those that can leverage customer histories with third-party market intelligence in more innovative ways are best positioned to beat out the competition and increase sales with current customers while expanding into new market segments.