MarTech Interview with Ryan Johnson, Chief Product Officer at CallRail

Ryan, we’re delighted to have you at MarTech Cube. Can you please start by sharing a bit about your professional journey?
My professional journey began outside of the technology industry – with a focus on accounting and finance early on in my career. While the transition from accounting to a career path involving AI sounds like a big leap from one another, the way my path unraveled makes sense looking back.

In college, I had the opportunity to take a computer science class, and it instilled a passion for working with data that I didn’t even realize I had until I was embarking on my career path. As I progressed in my professional journey, I realized I was passionate about turning data into something valuable for customers – particularly from a product lens. This passion is what ultimately drove me toward a career in tech working with AI.

While my career started one way, it was ultimately my deep interest in using data to help solve the complexities of today’s business landscape that steered my professional journey in an entirely different direction, bringing me to where I am now.

What are the key features of Convert Assist, and how do they specifically benefit small and medium-sized businesses (SMBs) in their marketing and sales efforts?
Developed by CallRail Labs, our innovation program which helps to bring AI capabilities and results into the hands of SMBs, Convert Assist uses AI to equip SMBs with the power to turn their conversations with customers and leads into actionable guides and responses.

Convert Assist has three main features:

• Action plan – analyzes call content to offer businesses actionable next steps for every lead, ensuring there’s always a follow-up and helping to increase lead conversion.
• Call coaching – analyzes a business’s calls to offer more immediate and personalized feedback on how to enhance the customer experience including areas of success and ways to improve.
• Smart follow-up – drafts personalized messages based on businesses’ conversations, offering a time-efficient approach to customer satisfaction.

When it comes to SMBs, many are seeking ways to enhance their strategies that allow them to work smarter without overcomplicating things. Convert Assist does just that, allowing SMBs to simplify their marketing and sales efforts by streamlining processes – from providing near real-time feedback that can enhance future calls to crafting ready-to-use follow-up messages – and improving the customer experience by ensuring that details, no matter how small, don’t fall through the cracks. Providing a personalized experience for each interaction. Convert Assist facilitates the next steps for SMBs, alleviating the burden off their smaller teams by guiding them in approaching typically more complex tasks.

Convert Assist doesn’t just empower SMBs by enhancing their processes, it also enables them to bring their customers and leads the quick and personalized experiences they’re seeking, which in turn allows them to turn more leads into customers.

Can you explain how CallRail’s AI-powered lead intelligence platform integrates with existing workflows and leading marketing and sales software like HubSpot, Facebook, Salesforce, and Google Ads and Analytics?
We want the power of our conversational AI to be easily accessible to our customers who rely on other martech platforms so that they can reap the benefits of our unique conversation data by fitting it seamlessly into existing workflows.

Currently, our conversational AI data is already being sent to over a dozen of the CRM and communication platforms in CallRail’s ecosystem including: HubSpot, Salesforce, Zapier, Mailchimp, Jobber, Unbounce, Google Looker Studio, MyCase, ServiceTitan, Freshpaint, and API/Webhooks.

These types of integrations empower businesses with the ability to do things like:

• Automatically create an AI-generated follow-up email after a call and send it directly to their email platform to get sent out.
• Receive AI-generated next steps from a call that are then automatically saved to the customer’s record in their CRM, allowing company stakeholders to remain informed on status without any additional effort from the team.

For example, with our Mailchimp integration, users can pull in the sentiment of a call to their existing workflows – taking their automated follow-up messages to the next level by determining the appropriate message to send based on that specific call. In instances where a call has a negative sentiment, users can set it up so a follow-up message inquiring how customer satisfaction can be improved upon is automatically sent out.

What challenges did you face while integrating with these major platforms, and how did you overcome them to ensure seamless functionality?
We’ve been ahead of the curve when it comes to the data that we send to these martech
platforms so, for many of these, we already had existing integrations set up which minimized potential challenges. It was less of a matter of getting integrations set up and more of an update to the data available on these platforms.

Since we already had the foundation in place with many of these platforms, we really just needed to work together to ensure that each platform had a place where they’d be able to store this new data.

The action plans feature is intriguing. How does it work to convert conversational data into actionable steps for businesses?
Action plan is a feature I’m very excited about! We’re always seeking ways to ensure our solutions power our customers to solve real challenges their businesses are actually facing, and this feature helps us bring that mission to life.

Action plan leverages voice AI to collect insights that stem from discussions by analyzing call transcripts, following calls the large language model (LLM) is prompted to act like an assistant – handling the next steps for users. Action plan pairs the insights it pulls from the transcript with data based on your business’ prior calls to auto-generate actionable next steps relevant to the specific instance and similar instances your company has previously dealt with.

This allows users to provide a personalized experience for each situation while using data-driven insights to further guide suggestions based on past customer successes.

Can you describe the process and benefits of automated content drafting for re-engagement, and how this feature helps businesses maintain customer relationships?
Our AI-powered solutions like Convert Assist use data, based on both current and past interactions, to auto-generate messages for users. Powered by insights gathered on calls with customers and leads, our solutions have a treasure trove of data that are then used to help produce ready-to-send messages that pull through personalized aspects based on each call.

There are two core benefits that come with using automated content for re-engagement:

• Increased time efficiency: The re-engagement process can be time-consuming, especially for SMBs with smaller teams. Using automated content allows teams to quickly create follow-up notes that pull insights directly from each call. This means teams no longer have to spend copious amounts of time trying to review their notes and synthesize call details before sending a message. Instead, teams are provided with a detailed follow-up that they can share almost instantaneously, reducing the time spent in the post-call process and allowing them to re-engage more quickly so they remain top-of-mind.
• Improved customer experiences: Improved customer experience goes hand in hand with time efficiency. In today’s digital world, businesses seek instant interactions in the same way they seek instant gratification from the solutions they’re using. Following a call, businesses need to be quick in re-engaging with their leads and customers, but being speedy doesn’t mean sending out a generic note just to get something out the door. Instead, automated content allows businesses to ensure follow-ups pull from previous calls to include specific and personalized details that’ll make the messages stand out to customers/leads and show a deep understanding of their goal.

Taking an automated approach to content drafting allows businesses to help nurture leads while also ensuring your customer relationships blossom. This approach allows businesses to build up a repository of historical knowledge for each customer that can then be used to further supplement future engagements, bringing customers’ interactions that place them and their needs at the forefront.

Call coaching sounds like a game-changer for front-line agents. How does this feature enhance their performance and contribute to better customer interactions?
Call coaching is another feature that I find really exciting and extremely valuable. At a high level, call coaching analyzes calls in near real-time. This analysis is then used to provide feedback on your business conversations to help guide future interactions and bring customers the most optimal experiences.

Leaders can use call coaching as a tool to truly empower their teams. This feature provides feedback on the areas that are working well – giving intel into where agents’ successes are including clearly articulating offerings or providing useful answers to a caller’s questions – so agents can implement a similar approach in their future calls. It also helps to pinpoint where improvements can be made like opportunities where highlighting specific examples can help agents showcase their experience and build caller confidence. This feedback provides agents with actionable insights on where they can improve without any delays in the feedback process.

Agents are often dealing with high-volume calls and it’s easy for feedback and small details to get overlooked. Call coaching reduces these instances by helping to immediately remediate any areas that need improvements, that way agents can quickly address things as they happen which in turn allows them to level up professionally. It’s easy for agents to get caught up in reading off scripts but this comes across as robotic and off-putting to callers – call coaching allows agents to feel prepared to be active listeners on their calls, allowing them to anticipate what’s next. With the capabilities to become an active listener, agents can more easily identify caller cues and engage with callers based on what they’re actually looking for vs. just following a script.

Call coaching brings agents the insights and resources they need to not only succeed in their role but to also further enhance their interactions with customers by offering callers the guidance and support they’re seeking.

Can you provide examples of AI-surfaced insights that have helped businesses optimize their marketing efforts and achieve better results?
Convert Assist equips our customers – across a range of industries – with powerful insights to move them toward their marketing and overall business goals.

This includes making it easier for customers to re-engage with leads, so they can maximize interactions and costs. Convert Assist’s ability to auto-generate feedback in near-real time also helps to pick up on things that may typically get overlooked during the usual feedback process.

Some direct ways Convert Assist is helping our customers transform their marketing efforts include:

• “One of our goals is to improve the customer experience while on the phone. As part of that goal, we provide phone training to all our service advisors and store managers. With Convert Assist’s call coaching feature, we get real-time information that enhances our phone coaching efforts. It doesn’t seem too far off that CallRail could eventually replace the need for a dedicated sales consultant.” – VP of Operations at an Auto Repair Business
• “Especially for prospect calls, we find the smart follow-up feature to be a significant time-saver and very supportive. It helps draft emails by providing a concise summary of key points to focus on. We’ve noticed that the follow-up emails generated need minimal adjustments compared to our previous templates. They’re more effective because they not only include our standard content but also capture the specifics of each individual call in real-time. This eliminates the need for third-party AI tools or additional applications.” – Manish Sharma, Digital Media Program Analyst at Choice Homecare

As a leader in product development, what personal strategies do you rely on to stay innovative and meet the evolving needs of your customers?
Part of my role as a product leader is to be continuously monitoring the tech landscape and having a close pulse on the latest trends that we can implement to further enhance our customers’ experiences. The key to staying innovative and keeping pace with customers’ shifting needs is pairing this knowledge with an approach that places your customers at the center of everything you do.

At CallRail, our mission is to make it easy for businesses to market with confidence and this customer-centric approach flows throughout our organization – from our leadership down to our solutions. I’ve found that the most critical part of developing this type of customer-centric strategy starts directly with your customers and customer feedback is integral to this approach.

If your end goal is ultimately to design solutions that help solve a problem for your customers, then you need to know exactly what kind of challenges they’re facing as well as the pain points they’re having with current solutions. Customer feedback sheds light on these obstacles and also helps to pinpoint areas where solutions may be causing more headaches than they’re solving for. It isn’t about just creating a solution and getting feedback from customers on it afterward either, it’s about bringing your customers in on the development process to have them weigh in on what will be most useful for them in this current moment and what’s working or, even more importantly, what’s missing. That’s why we established CallRail Labs – to ensure that we’re getting feedback from our customers early on and allowing them to have a critical role in the development process.

Establishing this kind of relationship builds a feedback loop giving businesses direct insight into how customer needs are evolving in real-time while providing valuable intel into what specific updates are needed to help address these changes.

Finally, is there anything else you’d like to share about the future of AI in marketing, your vision for CallRail, or any advice for businesses looking to leverage AI in their strategies?
For SMBs, the initial process of implementing AI can feel like a huge lift, but don’t let this steer you away from adding AI into your processes. When it comes to AI, the biggest mistake a business can make is adopting the first solution they come across just so they’re able to say that they’re “using AI.” This approach leaves businesses unable to see the ROI on AI they seek and often leads them back to the drawing board. A successful approach to using AI places time and resources behind finding the right solution for your business – not just viewing it as something to check off your to-do list.

Take the time to carefully consider the variety of options available to you, there’s a lot of different AI tools on the market these days each with their own unique set of capabilities! By taking the time to find the right tool for your business needs and goals, you’ll be well positioned to reap the benefits of AI – from boosted productivity to optimizing processes – while avoiding getting stuck in the implementation phase.