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Home / Insights / Blog / 3 Ways to Use Predictive Analytics for Customer Experience
May 28, 2020 - by Synoptek
The pace and scale of technological advancement have transformed the business landscape in several novel ways. One technology that has caused substantial disruption is analytics – especially in the field of predictive analytics. Today, organizations across the globe are leveraging predictive analytics to understand customer needs, detect anomalies in equipment, forecast inventory, identify risks and opportunities, and more.
What promises does predictive analytics offer for customer experience? Let’s find out!
Customers today have more options than ever to satisfy their needs; switching products or even brands have become extremely easy for them. Add to it the power they hold to influence businesses using social media and online reviews. Offering feature-rich products that are modern and innovative and meet the growing demands of today’s customer is no doubt extremely crucial, but do you drive as much focus on ensuring a fulfilling customer experience?
Over the last few years, customer experience has become every organization’s top priority. The impression brands leave on customers has a significant impact on what they think of the organization – across every touchpoint. Today, customer experience is critical to the sustained growth of a business. Positive customer experience can not only make customers happy; it can also help strengthen relationships and loyalty – therefore, helping bring in additional revenue.
When it comes to enhancing customer experience, predictive analytics is a gold mine. As organizations seek to nurture more relevant and meaningful connections with consumers, predictive analytics allows them to create (and sustain) a customer experience that is tailored to each individual’s distinct preferences and needs. Predictive analytics can:
Predictive customer analytics is empowering organizations to be proactive and personalized so that they can offer a seamless experience across the customer journey. By consolidating customer data across various touchpoints, they are tweaking strategies, so they can predict customer needs even before they know it themselves. Here are 3 ways to make the customer experience more efficient with predictive analytics:
Given how difficult acquiring a new customer is (and how much more difficult it is to retain them), predictive analytics can help analyze every interaction the business has with a customer in a bid to know the customer better. Analyzing data from social media, service desk interactions, sales team communications, or online reviews is an excellent way for organizations to read their mind, gauge their needs, and offer products that best fit those needs.
Predictive Customer Analytics Example: Beauty corporation Sephora uses predictive analytics to create personalized profiles for customers based on past purchases and recommends products they would need.
A poor customer experience is a significant reason for customer churn. Identifying customers who are dissatisfied or unhappy with the brand poses a higher risk of switching to another brand. Organizations can leverage predictive analytics to identify risky customers and then find ways to retain them.
Predictive Customer Analytics Example: E-commerce giant Amazon uses predictive analytics to detect issues customers face and provide new tailored experiences that overcome existing challenges.
No two customers are alike, therefore, there is no reason why organizations should consider the same strategies to pursue them. Predictive analytics can allow companies to understand every customer’s individual needs and personalize content across marketing offers, promotions, and campaigns to increase satisfaction and boost revenue.
Predictive Customer Analytics Example: Online streaming company Netflix leverages predictive analytics to provide personalized recommendations to users based on what they would like to watch next.
Big data and analytics have been one of the most disruptive technologies in history, impacting practically every sector. As these technologies leap forward, they present organizations with a slew of opportunities in the avenue of customer experience. With new tools for capturing and analyzing data, predictive analytics can help organizations transform the vast ocean of customer information and turn it into valuable insights, action steps, and outcomes for a superior customer experience.
To explore the predictive analytic tools available to you today, contact a data insights expert at Synoptek.
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