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VoiceOps — the #1 AI platform for analyzing enterprise voice
The richest data source about customers — their conversations — is the least accessible. Our mission is to provide easy access to customer conversations, and make voice data queryable. Our product analyzes the content of sales and support conversations and generates insights on phrases that maximize successful outcomes.
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@rrhoover Thanks Ryan! Our customers typically have short sales cycles, so the feedback loop for understanding how to properly adjust call behavior is pretty immediate. We're looking at a team's highest and lowest performers (and team averages) across a variety of core skills to understand what is most successful for that company.
If your highest performer is asking 7 probing questions on a call and focuses on describing benefits instead of features, that's helpful information that we can share with managers and other sales reps.
And you're right, sometimes it isn't about what you say, or even how, but when. We help show why the timing of a specific statement or question (like an upsell or close attempt) can change its effectiveness.
@rrhoover agreed, this is super interesting! Really hoping VoiceOps has a OkCupid style blog, I'd be curious to hear how high level features (i.e. Salesperson gender, accent, etc) affect sales in various industries🤓 (in addition to pitch-related insights)
Congrats on the launch!
What are you seeing as the biggest benefits sales teams get from using VoiceOps?
@eriktorenberg Hi Erik, and thank you! It's an exciting day here :)
1. 80-90% less time spent by managers preparing for coaching or performance feedback
2. Improved buy-in from reps because there's transparent data into behavior and call trends
3. Increase in successful close attempts => increase in closed sales
VoiceOps looks awesome! There have been a few related tools come up, but nothing as integrated and actionable for the purpose of selling.
@dariaevdo do you think startup teams just getting started with sales could use this to help from the early days? (yep—that's our current situation 😉)
@kunalslab Thanks Kunal! VoiceOps helps teams understand and scale the most successful call behaviors to their entire team, so to that end, it's something almost any transactional sales team should benefit from using. We've found that teams with larger sales teams get the most benefit in terms of time saved, but one of our favorite (and most vocally supportive) customers is a small company with a team of less than 20.
@dariaevdo Makes sense. I love this as it relates to creating a sales playbook. Mark Cranney describes it really well, especially in his a16z blog posts.
@dariaevdo @sama Love this idea! It's been hard for companies to leverage sentiment from text, but with voice cue behavior, it could be much easier! Not only do I see an opportunity to leverage salespeople's call conversations, but as most companies are moving into the SaaS space, you could also leverage this technology for companies who have massive call support like: Amazon, Verizon, Comcast, United, etc. And that might actually be a bigger business for you with the same technology you already have.
Essentially, it could be a way to gage customer satisfaction instead of annoying customer phone surveys that customers never actually do after a phone conversation.
And I know this is thinking too far ahead, but if it works out for call support analysis after A-B testing, it would be amazing to build a secondary platform where companies compete for higher customer satisfaction reviews based on your analysis data. That could be SO much fun.
How accurate is your voice recognition and does it handle accents? Are you using nuance, google voice, etc or did you make your own? Any API for it?
Nice product, congrats to the VoiceOps team. What sort of sales teams do you think could benefit most from VoiceOps? (EDIT: disclaimer I know the VoiceOps team and kind of knew the answer to this already, posted the question as thought would be a useful a public answer.)
@jacobtref Thanks Jacob! The teams that we're seeing benefit the most are ones that have a high velocity sales cycle. Our data allows for a very tight feedback loop, so companies with inside sales teams that typically close in a single call are able to see adjustments and improvements to their call performance much faster.
Congrats on the launch! This is an amazing product! There's so much money spent in sales optimization over email, and nothing in calls... And alls are way more effective for sales!
What has been the biggest challenge while working on this?
Best of luck and keep up the good work!
@pamevls Great question! The biggest challenge is making sure we're analyzing call content in a way that's actionable. There are a handful of other companies attempting to analyze calls, but very few are providing data that's clearly coachable and designed to help show longitudinal performance trends.
The other thing we have to keep in mind is that Sales teams operate differently from one company to the next, so the output has to remain flexible while also holding true to a core set of beliefs for what makes a sales team successful.
Hello hunters,
I’m Daria, the CEO of VoiceOps. We’re part of the YC W17 batch (previously known as Clover Intelligence). Huge thanks @Sama for hunting us!
Designed for enterprise sales teams and leveraging a form of AI (natural language processing), we’ve built a product that does in an hour what currently takes sales managers days - understanding what their team is actually saying on the phone.
We transcribe, parse, then analyze calls for what behavior is most successful (e.g. how many probing questions to ask on a call, the value of describing benefits vs. features, when to time an upsell or close attempt, etc.). Once we understand what works, we help managers scale that out, improving performance across their entire team.
We built VoiceOps because there’s a clear lack of visibility into calls and call data. Every other part of the sales stack (email especially) is already data driven, but sales reps spend most of their time on the phone, so it makes sense that it's the most important activity to optimize.
We’d love to hear your feedback and happy to answer any question!
@Daria Regarding the machine learning mechanisms and behavior, can/are you accounting for biases such as gender bias? Meaning what phrasing and/or words work with different demographics. Interesting from even a sales perspective for companies to appeal across demographics
@dariaevdo Amazing! I would love to test out the tool and interview someone from your team for my sales podcast called World of Sales: https://itunes.apple.com/ca/podc...
I would love to interview someone from your team and create a blog post about the main functionalities. Let me know if you would be interested.
@m_vukas would be happy to! Will reach out to you via email or feel free to follow up directly daria@voiceops.com.
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