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Cresta Executive Interview

Zayd Enam, Co-Founder and CEO, Cresta


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This is a year like none other, with many onsite conferences either cancelled or rescheduled. To keep contact center professionals informed, CrmXchange is conducting interviews with forward-thinking technology suppliers.

The rising artificial intelligence insurgent firm, Cresta, was founded with the goal of using the technology to transform how users learn high-value skills. Cresta offers solutions that provide guided selling responses, personalized real-time coaching, workflow automation and improved managerial visibility and control. CrmXchange Managing Partner, Sheri Greenhaus, had an exchange of ideas with Cresta Co-founder and CEO, Zayd Enam.

Below is the Discussion

With more people adapting to a work-at-home life, things have become more difficult.  Agents can no longer tap the shoulders of their peers to get answers and don’t have the tacit knowledge made possible by having others next to them. Thus, it is harder to share information.

This timing has been a factor in Cresta’s ability to ascend in the market. We’ve seen a boost in business. Many retailers initially had to shut down in-store operations, forcing them to sell via digital channels. Customers have been embracing this shift, but often have questions they need answers to before purchasing, particularly about products such as a mattress or a high-end guitar. With many customers unable or reluctant to go to a store, we’re finding many businesses converting their in-store salespeople to online salespeople. The question then becomes how a retailer enables them to make this transition and become more effective online communicators. We’re able to help with that. Retail is one of our key target verticals, along with telecommunications and software-as-a-service.

Our AI software provides real-time coaching on what agents say. Results can be dramatic. Our solution enhances the effectiveness of the digital channel by giving customers the best answers to any questions they have before making a purchase. It’s a tool that is well positioned to meet the changes in this economy. One of our post-Covid customers was able to achieve a 24% increase in sales over two weeks.

To start, we assess the status of a business’ chat agents. We review conversations over the past year to learn the behaviors and responses that led to successful outcomes, whether the result was a sale, a higher customer satisfaction score or elevated NPS. We use these productive conversations to train a model that learns from these successes. Once the model has assimilated the information, we deploy the positive actions to every single conversation. For example, a new rep gets a prompt telling them what to say at specific points in an interaction. It’s about a two-week onboarding process. We engage with the company, work with the existing contact center (voice or chat infrastructure) to get the data to train the model.

The AI is constantly learning, leveraging every conversation. Starting with the collective knowledge of the past year, the AI gets better every day. With companies being forced to shift to an all-online sales model, we bring the chat solution and the people together. We partner with leading chat platforms and contact center infrastructure companies in the space, such as Avaya or Genesys, as well as CRM providers.

We are predominantly focused on sales as they are easily measurable and the ROI is clearly identifiable. Once we prove the value of the product, we also see productivity gains among the reps using it as well as CSAT improvement. Enabling the rep to better respond with product-specific knowledge and guiding them on what is the best action to take to resolve the customer inquiry reduces AHT and improves CSAT.


Coaching is another value proposition of Cresta software. The way it works is that the system identifies the strengths and weaknesses of individual agents, pinpointing the behaviors that the agent is performing or not following through on. For example, it might point out that an agent we’ll call “Jasper” might not have been asking the proper discovery questions, taking the right steps to overcome objections, or not effectively pitching upsell products. The solution will then identify the behaviors of top reps which Jasper isn’t following and then create a personalized coaching plan for him. So whenever there is an opportunity to take these actions, it coaches him to apply these behaviors.

The system is constantly learning.  We can demonstrate at least a 10% lift at the outset with customers with whom we work and as much as 49% lift as we’ve experienced with some retail customers.  What happens is that as the system continues to learn from every single interaction.

Agent Buy-In

While agent buy-in can be a problem with some solutions, it is not for us. Agents seem to love the product. There’s always been a focus for Cresta to ensure that the product really helps at the agent level experience. We think about our products in several different ways: it helps agents have better conversations by coaching and prompting them on the right things to say. It also has features that make their lives easier, such as automating some of the tedious bits of their work. They can just click on one thing and save themselves multiple keystrokes. Helping them with small things like that are really appreciated, which contributes to the buy-in. It also makes them want to use and learn from the solution. In addition, we have a gamification component in our coaching application. So, when an agent displays desired behavior, we follow up with a reinforcement statements, such as “Great job following that hint.” Using the software helps reps meet sales quotas and earn commissions. Since we can demonstrate to the company how often reps are using the software, some have made this adherence part of their compensation structure.

How Cresta Started

I got involved while doing a PhD at Stanford on artificial intelligence, which involved projects working with self-driving cars. I realized that the time it would take to bring that technology to the world was still far on the horizon. It was apparent that the right environment to use AI to help people would be in an office setting. We’ve all heard the hype that that AI is going automate jobs away, but I see it is a tool. We couple the software with human capabilities to create a more effective combination. And if you can build AI to assist people in doing better, that is a more appropriate use of the technology; one which meshes with my particular set of passions. We saw the contact center space as an industry where we could help people work far more effectively. Can we help people be 10x as fast and 10x as good? That was my thesis, my PhD work. So, we started working with companies and immediately identified it as a major opportunity. Working in an academic lab wouldn’t allow us to build the technology and deliver it. With my PhD professor as co-founder, we dropped out to start the company and bring our research to the world.

My original exposure to the contact center world was learning that some 15,000,000 people were involved in it, with a significant percentage of Americans and all over the world in these positions. There is no Microsoft, Google, Amazon, or Uber in the contact center universe to provide truly exceptional customer or agent experiences. The industry is quite massive and the problem complex. We saw a chance to become a dominant force in the industry by applying AI technology.

The current situation has caused many companies to shorten their timeline for adapting AI. Customer experience was already a major point of differentiation before this all started…now it’s something brands will either win or lose on in the market. Twenty years ago, it may have been acceptable if someone had to wait two hours to talk to their bank or airline carrier. But now, when they are comparing their experience, it is not to other banks but to Amazon. Now that people know what a truly positive experience is like, expectations have gone way up.  Consumers feel they have a right to really great support, a positive sales process that is frictionless. For the truly savvy companies moving forward, investing in AI is a strategic differentiator which will be key not only to their survival, but to their growth.

There will always be functions that will be automated in the contact center space, such as FAQs and order status. But there will also always be a strategic role for folks in the contact center. This role will be upskilled to be a relationship builder between a brand and the customer. The strategy-oriented companies with an interest in building such relationships will understand the value of investing in the reps who can maintain them. That’s where we are headed. At the end of the day, it’s about people having conversations with each other. But how does a company help its reps have as many productive conversations with customers as possible?

The most important thing I would like contact center managers and executives to know is a simple premise. Artificial intelligence is a tool that helps people be better.  If companies focus on the technology for the right use cases, it can become something that is a massive win for everyone. Rather than automating contact center jobs, it will make people better.