Predictive analytics is on the rise. Two years ago, retail chain Target was able to find out a teenage girl was pregnant before her father even did. While this revelation sparked controversy around issues of user privacy, the incident demonstrates the power of data.
Data can also predict user behavior. Google Calendar, for instance, absorbs user information and can predict where you will be and what you will be doing on a given Tuesday afternoon.
But data’s ability to anticipate and understand human behavior is not limited to business-consumer interactions: it has the ability to implement much-needed change in the way we engage with customers in general.
In the past three decades, customer software systems have been built to automate tasks, streamline operations and cut costs. This has created a culture focused on increasing operational efficiency rather than one aimed at customer happiness.
But in a world where services are leased, not owned, where customers can leave at a moment’s notice and go to a competing service, the old way managing customer relationships with guesswork, not data, isn’t going to cut it. SaaS companies need to be aware of how data can transform the entire customer journey, from determining potential customers to closing deals to keeping those customers happy in the long-term.
Take a look at these three areas of the customer journey and see how data can change how you approach customers relationships:
Pre-Sales: Select Customers Who Need Your Service
Moving and storage company PODS hired Target Data, a marketing and analytics firm, to develop better sales leads. Target Data was able to build a model that could predict with 75 percent accuracy the likelihood that a home would sell in one, two or three months. This kind of data lies within most software companies’ reach. By digging into usage numbers in your own systems, you can determine which customers need your services -- and how to best reach them.
Sales: Begin the Customer Relationship
Sales is traditionally seen as the final stage of marketing. Big data has the potential to make sales smarter and more efficient by predicting not only who is looking to buy, but which deals have the greatest likelihood of closing successfully. Relationship intelligence platform RelatelQ, recently acquired by Salesforce, is able to say, "Deal X has a 80 percent chance to closing by the end of quarter because you did Y and the company is going into Z market." Data powered insights like these will only increase the likelihood that sales will close and continue to attract more users.
Post Sales: Ensure Customer Happiness
Software development company Zendesk wanted to change the approach to customer service, noting that it’s traditionally generic and reactive. With 40,000 customers in 140 countries, their success and growth depended on customer retention. Studies show 90 percent of customer turnover for SaaS companies is the result of poor product usage, which indicates that the ability to maintain customers rests in the hands of customer success reps.
Utilizing powerful data analytics tools, Zendesk was able to improve their retention pipeline: They analyzed buy and churn signals, which allowed them to see which accounts needed the most help. As Zendesk prepares to target larger companies and build its customer base, data will be key in allowing the company to understand which customers need attention and when, without even having to ask.
Today, smart software has an opportunity to change everything. By applying data driven insights to understand what customers are really looking for in a service -- rather than focusing on what your business needs -- smart software can transform the entire customer experience. It can empower employees to delight customers by simply being smarter, predicting needs and individualizing the experience.
Have you ever used data in customer relationships? Sounds off in the comments below!