How Predictive Is Your Service Organization?

In a traditional service organization, when a customer is unhappy, you rarely hear from them. They simply stop using your product or service, you don’t know about it and you don’t know why.  As products become more commoditized, and good customer service is an expectation, companies struggle to continue to find ways to differentiate themselves on relevant experiences other than response time.

So what’s the difference between the companies you love and other businesses?  We don’t love companies we have transactions with. We love companies we have relationships with.  There is mutual trust.  As companies strive for brand advocates, customer centricity and loyalty, organizations need to build a foundation on personal relationships with their customers.

Our days of waiting for customer’s to contact us are close to being over.  In today’s “know me” society driven by instant gratification, companies find themselves playing catch up and reacting customers demands.

  • They are hiring staff and waiting for customer to complain and tell them about their issues.
  • When customers to contact them, they are often unprepared to resolve for customer problems.
  • And they are not leveraging all customer data points to paint full picture of who a customer is and the value they bring to the company.

But how do they do this?  What metrics do you focus on?  How do you organize your operations?  The marquee service goal of too many companies is the time to respond to a customer.  In the age of customer experience, customer engagement, and every other customer term, analysts spend their time redefining, while companies still remain fixated on how to reduce Average Handling Time, or how long a customer is on hold, or how fast an agent can respond to email, or even how fast can they can get a field technician to a site to fix a problem.  Organizations are focused more on the ‘ME’ and less on the ‘C’ in managing relationships.

In our work with our clients, we’ve found that the problem with response time is it becomes increasingly difficult to measure a competitive advantage by trying to make these improvements.  That’s not to suggest we shouldn’t respect the time a customer spends interacting with a company, rather admitting to ourselves that decreasing response times means more to internal operational savings, and has minimal advantages to the customer.

Companies need to focus all resources, not just people, but also their data, the infrastructure, and designs to be less responsive to customer demands, rather predictive of their needs.

  • They do this by blending not only customer data related to issues, but also their order data, product data, and marketing insights.
  • They do this by analyzing all channel interactions to identify patterns where trends can be further evaluated.
  • They do this by then applying engagement rules based on their data to monitor and trigger customer insights ahead of the curve.

By leveraging customer related data, companies can gain better insight to develop the most impactful strategies to take the right actions and focus on customers problems you can actually predict. With the right information and right data, you should not only be able to predict customer issues, but understand their behavior as well.

predictive_service_monaAmberLeaf has spent the last few years working with our clients to help build relationship-based models by using data for Predictive Service.   By adopting a Predictive Service model, organizations shift to focus on checking things that might go wrong, monitor for behaviors that you weren’t aware of, and provide insight into the health of your customer base.  In this model, you can use your data to show any early signs that a customer might be struggling with your organization and reach out proactively to see how they are doing.  With Predictive Monitoring, company behaviors shift to an outside perspective inward.

In a Predictive Service model, your business becomes dependent on advocates and your service professionals need to ensure that your customers have the help they need to be successful.  And turning ALL your customer data into actionable strategies is ingrained within the policies and procedures of your operations and not a luxury.  Predictive Service allows you to:

  • Review and react quickly to changing customer dynamics.
  • Forecast and plan product needs, service levels, and work force management demands.
  • Drive product and service decisions based on analysis that customers aren’t telling you.

A Predictive Service model moves to build the business around the data, where you we are able to preserve the data and ensure you don’t have problems with it.  The model builds on your traditional operational related reporting (average handle time, CSAT, customer effort) and moves towards the goal to bring the voice of the customer directly to your daily business decisions.  Even with departments of a company that are typically not customer facing.

The marriage of relationships and data is the catalyst that propels a Predictive Service model.  When you see something in the customer’s data and reach out to them, they shouldn’t view this as intrusive rather as a confident, partner, and not a vendor or provider.   Your customer data should enrich the relationship and allows for prediction and insights.  Some of our most progressive clients adopting a Predictive Service model believe that ‘if you have data that will help your customer, it is your moral obligation to use that data to support your customer.’  We firmly believe this, and it also simply makes good business sense.  You will delight your customers.  You will decrease operational costs.  You will develop a true competitive differentiator.

AmberLeaf (www.amberleaf.net) combines strong business and operational planning with innovative technology solutions to ensure our client base serves the right customers in the right ways to generate the greatest return. To learn more about how we can help your company improve customer experience, contact us at 312.474.6120, or info@amberleaf.net.