How To Identify Sales Leads With Data Analytics

Arooj Fatima
Arooj Fatima

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Finding leads is a challenge that all salespeople must overcome in order to succeed. Thankfully, analytics can lessen the struggle for sales teams.


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There are key indicators that lead to a successful sale. These indicators often come from captured data when generating leads. They can include specific customer profiles, key actions, or the duration of a sales cycles that produces a repeat purchase. By capturing the right data and properly analysing them, sales teams can identify quality leads to improve sales conversions.

In this article, we take a look at how some companies leverage on existing data to tap into new markets, generate leads and improve sales.

Harness geographic and demographic insights to identify SALES OPPORTUNITIES

Understanding the geographic and demographic data of existing customers provides new insights and opportunities for sales and marketing teams. This process eliminates guess work and provides  clarity for decision making.

The Case of Frisco

According to a study by Frisco's Convention and Visitor Bureau in 2013, local search in the Dallas suburb isn’t just restricted to local residents. "Out-of-town" visitors perform a significant number of local searches, and actually spend more than locals.

The study revealed that:

  • The top three reasons for visiting Frisco are (1) business travel, (2) weekend getaways, and (3) youth sporting events.
  • More than 31,000 visitors visit Frisco and spend $3.9 million each day.
  • At that time, 24% of all people in Frisco are non-locals on any given day.
  • Visitors spend more than locals in categories such as food, shopping, transportation, gifts, and entertainment.
  • Visitors who attended arts events spend more than double as compared with locals.

These data points gave businesses in Frisco the opportunity to run online search ads to drive visitors to their stores and increase revenue. In the same way, your team can look at their customer's geographic and demographics data to identify new business opportunities.

Improving ROI with Recommendation Systems

To increase sales conversions, sales teams need insight into which products or services are attracting leads and purchases so that they can modify their message for each interaction. They can accelerate the process by leveraging on prescriptive analytics to recommend the best course of action depending on the customer's historical profile.

In the US, banks face increasing pressure to generate additional revenue from their existing customer base. Research has found that an average customer has 9 financial accounts across multiple banks, and 2.2 accounts with a single financial institution.

One US bank developed a recommendation system, which allowed sales teams to offer relevant products to customers. It analysed and scored the web and transaction data of all customers. Customers who met the scoring model threshold were matched with financial products that they had not yet purchased. These qualified leads were then fed into various customer touch points such as inbound/outbound call centres, email databases and the website. Additionally, the matching assessed the customer’s eligibility and calculated the dollar value generated by the product to the bank. By doing so, the bank was able to prequalify leads and increase the degree of certainty for its sales teams. 

gET mORE From Your Marketing Spend

By leveraging on data analytics, teams get more out of a marketing budget. Analysing existing data allows businesses to determine where leads are coming from and to optimize its spending.

The analysis allows for the determination of lead sources, and streamlining of marketing campaigns. Moreover, clean data empowers marketers to identify and fix problems within sales pipelines.

the Case of Panasonic

In 2015, Panasonic Japan successfully shifted from a product-centric advertising strategy to a customer-centric one. It used data analytics to uncover key insights about its customers. The main purpose was to increase customer engagement via digital advertising. At that time, each Panasonic product had its own advertising campaign, but the company lacked a single platform to analyse and report on performance across campaigns. They needed to create a unified view of all their campaigns in order to get a holistic idea on what customers wanted. By collating information into one platform, Panasonic was able to present customer data on a common corporate platform accurately.

The electronic giant then moved onto segmenting their customers by creating different profiles based on their engagement with different product websites. The analysis also showed what was most often purchased together, which allowed Panasonic to offer targeted recommendation to customers.

Panasonic Japan’s customer-centric campaigns have since witnessed an improvement in their 'Return on Advertising Spend' (ROAS) by 30%. Moreover, certain campaigns saw click-through rates increased by 300% year on year, while bounce rates declined by 50%.

Conclusion

Given the right access data and insights, marketing and sales team can populate database with high potential leads. Objective-driven data analysis helps create accurate buyer personas which allows its users to better understand the characteristics of their customers. If you’d like to learn about how you can generate sales leads with data analytics, do check out our custom feasibility report today.

 


 

ABOUT DataVLT

DataVLT is an affordable, on-demand analytics platform secured by blockchain technology. It is designed to simplify the complexity of data science. Backed by artificial intelligence and machine learning capabilities, DataVLT empowers enterprises to make meaningful sense of their big data and scale cost efficiently. Essentially, it is an end-to-end data/information management platform.

Learn more at www.datavlt.com

 

 

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