What Will You Discover?

Uncover new insights in your customer conversations with Signal Discovery
Signal Discovery Persona - VictorInvoca Signal Discovery Persona - NoahInvoca Signal Discovery Persona - Mia

Tap into a gold mine of actionable first-party data

Powered by unsupervised machine learning, Signal Discovery gives you an unprecedented view into one of your most personal buyer touchpoints. With customer conversations automatically grouped into topics based on similarities in speech patterns, you can quickly gain new insights from tens of thousands of conversations and take action on them in real time — all with the goal of driving more revenue-generating calls, boosting conversion rates, and optimizing the buying experience.

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See What Victor, Noah, and Mia Discover

Learn how Signal Discovery helps three marketers explore the previously-uncharted world of customer conversations, and find out how they turn these new insights into big business results.

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With cleaner, more refined conversion data in hand, Victor drives more high-intent callers and reduces his customer acquisition costs.

Victor is the senior manager of paid search at LimitlessTel. By all accounts, his conversion rate for "appointments set" looked great, but the average revenue was low and cost per conversion was high. There was room to improve, he just didn’t see how.
See what Victor discovered

Victor's Discovery:

Victor was surprised to learn that there were three distinct types of appointments being set. Topic 2 showed that a majority were new service appointments, but from topic 5, Victor learns that 33% of calls are technical service appointments being scheduled in the sales contact center, which he didn’t even realize was happening. Additionally, topic 16 showed that 14% of calls were to reschedule appointments. Prior to this discovery, Victor treated all appointments equally as inputs for his paid search optimization model.
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Victor's Solution:

From topic 2, Victor creates a new refined "appointment-set" conversion signal within Invoca and pushes new calls matching this signal into Google Smart Bidding — replacing the previous broader and less accurate conversion signal. This ensures that he is only optimizing for high-value new customer calls, not for customer service calls or rescheduled appointments.
See his results

Discover Victor's Results:

With Google’s machine learning using the refined conversion signal, it automatically begins bidding on high-performing, lower cost keywords. This provides a 15% lift in conversions month-over-month and a 27% drop in cost per conversion. Victor proves his star-status on the team, and his boss’s boss suddenly knows who he is. It’s a good day for Victor.
  • 15% lift in conversions
  • 27% drop in cost per conversion
  • Tiki cocktails with the VP on Fridays

Noah discovers new ways to increase conversion rates from e-commerce and inbound calls.

Noah is the director of digital marketing at H&A Mutual. His site conversion rates are low, but call volume from his marketing is solid. He doesn’t understand how he could be getting so many calls from the website while seeing no significant increase in conversions happening on the phone.
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Noah's Discovery:

Based on topic 21, Noah determines that 26% of callers aren’t able to find the policy information they need online, so they’re calling to get answers. Furthermore, he finds that based on topic 8, 22% of callers appear to be having trouble purchasing their policy online so are calling in.
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Noah's Solution:

Noah begins by using Signal AI to tag all of his new inbound calls with the "policy" topic in order to understand which web pages are driving the most policy questions. He then redesigns these pages to make it easier for customers to get answers to common product questions. He also simplifies the new account signup process, making it easier for customers to buy a policy online.
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Discover the Results:

By making it easier for people to find policy information and checkout online, Noah’s changes lead to a 35% increase in new policy sales across both ecommerce and the call center. By enabling buyers to do more themselves, Noah’s sales agents have more time to work with people who are buying new policies or increasing coverage. Noah is feeling pretty great when he announces the $500K increase in revenue over the last quarter!
  • 35% Increase in conversions
  • $500K Increase in revenue
  • 225% increase in office high-fives

Mia focuses on the new patient experience to increase appointments and decrease caller frustration.

Mia is the VP of digital analytics at Healthcare Enterprises and it looks like she has a new patient experience problem. Her call times are consistently over 22 minutes, and the percentage of calls that are turning into patient appointments is decreasing. She assumes that the call center agents must be doing something wrong.
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Mia's Discovery:

Mia was able to validate that many conversations pointed to a poor call experience but that it didn’t appear to have anything to do with the call center agents. Topics 62 and topic 44 pointed to an unknown IVR issue that was causing some customers to spend a lot of time on hold, get lost in the IVR, or get sent to voicemail. Based on topic 11, she also discovered calls were being transferred multiple times and often to the wrong agent. 
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Mia's Solution:

Mia immediately addresses the IVR issues causing caller confusion and long hold times. Using Invoca, Mia also implements priority call routing for high-intent callers who came through target paid search keywords to ensure that these new patients get immediately connected to the right agent, skipping the IVR — and long hold times — entirely. She also creates a new digital retargeting audience by combining topics 29 and 31 to reach callers who are inquiring about becoming a new patient but did not book an appointment.
See her results

Discover the Results:

Through the call routing changes, hyper-targeted advertising, and proactive monitoring of new patient experience, Mia achieved a 37% lift in appointments set over a 6 month period. Priority routing and changes to the IVR also led to call wait times being reduced by 5 minutes on average and total call time spent with reps dropped by 25%. This increased conversion rates for marketing and was a big efficiency boost for the call center — and for Mia’s career.
  • 37% more appointments set over 6 months
  • 25% reduction in call time
  • A long overdue promotion
Signal Discovery shines a whole new light on conversations happening in our contact center, giving us the data we need to enact changes across the organization.
Noah Brooks, Manager of Digital Engagement and Analytics @ University Hospitals