Oct 26, 2020

Effective Customer Support is about Impact

In customer support, as in sales and marketing, countless solutions have emerged, promising new ways for companies to service, retain and expand a burgeoning customer base. With the advent of Artificial Intelligence/Machine Learning (AI/ML), there’s also a proliferation of new tools to this end, always accompanied by lots of talk about getting more done in less time.

These solutions unfortunately perpetuate an obsession of maximizing productivity through automation. Too many customer support tools nowadays achieve raw productivity at the expense of business impact.

Our vision for the future of support goes beyond this, and seeks to reframe support’s underlying purpose. The substance of speedy case resolution can be augmented with the impact that case has on our understanding of the customer,

The SupportLogic way

SupportLogic eliminates the bottlenecks that prevent customer support from turning customer interactions and case details into real and actionable insights and workflows. We bring advanced workflows enabled by data sciences (AI/ML/Deep Neural Network and Natural Language Processing) to the Support organizations to understand and respond to customer escalations, sentiment, and attention needs. The product automatically captures and analyzes all customer interactions in the case tracking/ticketing system. Before your staff ever sees a support ticket, the product has already analyzed and triaged it.

This means several things at once;

  • Our users can answer any support analytics question instantly with no engineering experience or data sciences work required. And whatever question you ask, the data is already there because SupportLogic tracks everything.
  • Our users can initiate tasks right from our intelligent applications for customer management, agent management, etc. and execute workflows while staying in sync with the underlying case tracking/ticketing system.
  • Our users save time and cognitive load with AI augmentation that makes their workload easier. Nobody could reasonably read, analyze, and digest the content of every case/ticket that an organization receives every day. We take that pain away.

By delivering instant results, SupportLogic reduces time-to-resolution, or better said “time-to-impact,” and enables direct action from within the product that will also be continuously updated in the underlying case tracking/ticketing systems. These are two key differentiators

The Go-to-Market Philosophy

This philosophy of delivering results to our users in customer support also applies to our go-to-market efforts. All of our positioning stem from the problems we’re trying to solve in the product and the role that Support plays at the heart of a customer-centric enterprise.

We want our sales process to become something akin to proactive customer success. Our best sales conversations are the ones in which we serve as their customer support consultants.

In these instances, the customer has installed our product (a process that should only take minutes), so on their first or second customer call, we’re already able to share insights that we’ve uncovered. We’re able to suggest that they might want to take a different approach to prioritizing agent workload, reducing backlog, preventing customer escalations, assigning/reassigning cases, investing in skills development, or focusing on particular customers that we can tell — based on the sentiment and attention insights — are important for the business.

That’s the most effective way we sell our product. Instead of leading with sales and marketing efforts, we are putting the product front and center with our target users. This creates a situation where prospects come to us pre-sold on the product and the value it can deliver. This changes the existing time-to-value equation into something much more organizationally advantageous.

I like to call it a “time-to-impact” equation.

Omid Razavi heads customer success at SupportLogic. Omid may be reached on twitter: @orazavi and omid@supportlogic.io

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