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How to Use Business Intelligence to Measure Customer Loyalty

by Cameron Graham, Editorial Coordinator, TechnologyAdviceMonday, June 23, 2014

It’s a lot cheaper to retain existing customers than attract new ones.

This time tested idea remains especially accurate in today’s market, where companies incur heavy losses from customer attrition. Banks lose an average of $45,784 per customer lost. Athletic apparel powerhouse Lululemon recently experienced rapid customer churn and saw their stock price fall from $80.41 on May 6, 2013 to $43.77 on May 5, 2014. Because of poor customer experiences, quality issues, and some scandalous statements by Lululemon’s founder, the company lost previously committed customers to industry competitors.

The first step in preventing customer churn is identifying important user behaviors. Companies should be observing primary demographics, spending patterns of target groups, and the factors behind customer loyalty. These figures can seem daunting at first, but many business intelligence solutions are specifically designed to analyze and segment customer lists, in order to identify high-risk users.

To optimize the usefulness of these systems, companies need to know the best data to observe, the best analysis methods to employ, and the best practices to implement. Through careful observation and strategic modifications, companies can effectively utilize their business intelligence solution to measure and increase customer loyalty.

Finding the Best Data

As the industry continues to improve, business intelligence companies are offering more modules for observing and analyzing data. While these can be informative, users must first understand what data to analyze before any observations can be made.

Start by capturing as much data as possible.

This might seem like overkill, but you’ll never know what blind spots you might be missing if you don’t give all the data a chance.

Important data to aggregate includes:

  • Customer demographics
  • Average amount spent by customers in each demographic
  • Percent of customers in each demographic who return
  • Period between purchases
  • Purchase medium (catalogue, internet, or brick-and-mortar)

While this list is by no means exhaustive, it’s a good starting place for making usable observations. For businesses that haven’t kept records in the past, this is a process that can start today. Gather as much information as you can about your customers as they make purchases. Record who they are, how much they are spending, when they make purchases, what they are purchasing, and any other information that could be significant to your company. As you continue this process, your business intelligence solution will use this data to reveal trends in who your customers are and what they want.

How to Analyze Your Observations

Now that you have collected the pertinent data, it’s time to analyze the information. By turning data into actionable observations, analysis is where business intelligence software can truly benefit your company. Beyond dashboards and reporting capabilities, many BI providers offer modules that are especially useful for observing customer loyalty.

Mapping Modules

Many business intelligence providers offer geography or mapping features for geospatial analysis. For companies with a large number of online sales, this can be used to display where sales are coming from by product and volume. Tableau Software offers interactive maps using common geographic fields like state or postal code, while giving users the opportunity to define their own sales regions for statistics about the location of buyers. By configuring the module to display return buyers (multiple purchases from the same IP address), companies can utilize this feature to determine geographical trends in customer loyalty, and target marketing programs around this.

Social Media Integration

Beyond your transactional observations, there is a wealth of information to be analyzed and observed from your social media accounts. BI providers such Datameer are able to take unstructured data from Twitter, Facebook, LinkedIn, or other social outlets, and analyze it for sentiment or trends. The findings can help identify customers who interacted with your businesses’ social media accounts, reveal purchasing behavior based on social media activity, and find customers who shared information about your business. You can use this information to increase strategic social media interaction, and reward loyal customers who post about your company.

Customer loyalty doesn’t have to be a trial and error process. Business Intelligence software can increase customer retention, and take the chance out of customer loyalty initiatives. When the process of acquiring a new customer can cost as much as five times more than retaining an existent customer, utilizing BI software to observe and improve customer loyalty is well worth the time and money.

About the Author:

Jesse Jacobsen is a web content writer at TechnologyAdvice. He covers business intelligence and analytics, along with other software. Connect with him on Google+.

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