Key Takeaways
In our recent webinar, we explored how intelligent conversation analytics is transforming contact centres operations. MaxContact’s Leah Tillyer and Conor Bowler demonstrated how our Success Intelligence solution empowers teams to enhance performance, provide personalised coaching, and drive better business outcomes.
The QA Challenge
Traditional quality assurance approaches are failing contact centres. Our research reveals that most operations:
- Review only 2-3% of calls through random sampling
- Struggle with clunky legacy speech analytics platforms
- Wait 48+ hours for insight synchronisation
- Miss valuable opportunities hidden in 97% of unanalysed conversations
Performance Benchmarks That Matter
Our independent benchmark survey of 500+ contact centre leaders revealed:
- Teams making more strategic calls (avg. 65 per agent daily) achieve greater success
- First call close rates average 28%, indicating training effectiveness
- Average conversion rates for campaigns hover around 7%
- Each successful call generates approximately £200 in revenue per agent
The Future of Sales Success: Smarter Listening
Success Intelligence delivers:
- Complete visibility across all customer interactions, not just a small sample
- Objective sentiment analysis to track customer emotions and identify coaching opportunities
- Powerful objection tracking to understand patterns and measure handling effectiveness
- Data-driven coaching insights to help agents improve faster without blanket training
Download the Slides
Webinar Transcript
[00:00:04] Leah Tillyer: Hello and welcome. I’m just going to let people join as
[00:00:14] Leah Tillyer: we just go through some housekeeping elements.
[00:00:20] Leah Tillyer: so, whilst people are joining, the session is being recorded, and it will be shared afterwards. So if you do need to drop at any point, don’t worry. It will be there as a playback.
[00:00:33] Leah Tillyer: We encourage questions throughout the session. So we run the sessions, live every single month.
[00:00:41] Leah Tillyer: and we encourage questions just so other people can learn might be something they were thinking about and wanted to know, too. And
[00:00:51] Leah Tillyer: yeah, if if you think it’s useful, and it will be useful for somebody else, too, please do feel free to share as well.
[00:01:01] Leah Tillyer: so I can see numbers are creeping up now, and I’ll just do some introductions.
[00:01:11] Leah Tillyer: So Hi, everyone, I’m Leah, I’m product marketing manager here at Max contact. And my role is all about understanding our customers. So just understanding what they need, challenges that are faced and how our solutions can help them to succeed. I work really closely with Conor and the product team and with the sales team and customer success and look at how we bring new features to market
[00:01:39] Leah Tillyer: hopefully ensure clear and compelling messaging, and help businesses to get the most value from Max contact and our technologies.
[00:01:47] Leah Tillyer: and Conor is on the call with me. So he is principal product manager at Max contact. He brings over 16 years of product leadership experience across a diverse technology range, including contact centre software, financial services and AI solutions as well.
[00:02:07] Leah Tillyer: His career began in engineering and development. He progressed through roles in professional services, pre-sales and channel management, a lot of variety, and I’m sure a lot of empathy across those different roles, and notably Connor launched A. b 2 b product that attracted over 15,000 clients. It secured patents for AI innovations
[00:02:29] Leah Tillyer: and it revitalised product from decline to growth, which is no easy job. So at Max contact. He leads a spoken product focusing on enhancing contact center analytics to provide businesses with actionable insights for improved decision making.
[00:02:48] Leah Tillyer: And so that’s a little bit about us.
[00:02:51] Leah Tillyer: and we have some existing customers on the call, which is good to see and a few new faces as well. So a little bit about MaxContact for anybody that doesn’t know us. So we’re the best Cloud Contact Centre software for delivering conversation outcomes and customer insights to generate more revenue compliantly, and our customers are across the sales collections and customer service space.
[00:03:20] Leah Tillyer: And they work with Max contact to build better and more intelligent contact strategies that deliver results. So
[00:03:29] Leah Tillyer: for our customers. Since working with us, they’ve seen talk, time, sales, conversion rates and debt collection rates double since working with us.
[00:03:40] Leah Tillyer: and at the beginning of 2024 we launched, spoken.
[00:03:45] Leah Tillyer: So we have over 4 million hours of transcribed calls and summarized calls, topics tagged, and sentiment tracked, and it’s quickly trending upwards as well, which is very exciting.
[00:03:59] Leah Tillyer: And at the beginning of this year we launched success, intelligence, and that is what we’re here to talk about today. So success, intelligence is conversational analytics for better sales, performance and customer experience. It provides visibility on missed buying signals, common objections, and, most importantly, objection, handling effectiveness as well.
[00:04:25] Leah Tillyer: but before we go into that we’re going to talk a little bit about what we see across contact centres, and why and how they’re missing valuable insights. And so we use speech analytics. The. This is how we gather our insights as a business. So we’ll play a little bit of QA Bingo and just see how many of these resonate with you.
[00:04:51] Leah Tillyer: In terms of how customers usually operate when we speak to them. They’re either already using a speech analytics software and that they’ve maybe had for a few years, or they’re doing things manually. So
[00:05:06] Leah Tillyer: if they’re manually listening to calls, they usually have an excel spreadsheet. Typically in front of them. They are having to look out for compliance elements. So was a direct debit mandate read out on a call. They’re looking for
[00:05:27] Leah Tillyer: legalities that might need to be said, and then on the flip side of that, they’re also looking at performance metrics as well. So
[00:05:34] Leah Tillyer: 2 very different things to look out for, and looking at how empathetic an agent was on the call. Did they actively listen for things that were being said, and 2 very different things to be listening out for. And I know when we’ve spoken to clients about this in the past, it’s often question time when they’ve got the headphones on. People are coming over. They’re asking questions. They’re having to stop, start the process.
[00:06:00] Leah Tillyer: And so it’s really time consuming.
[00:06:03] Leah Tillyer: And they’re not always capturing the things that they need to.
[00:06:07] Leah Tillyer: And then we have on top of that random call sampling. So they’re going through picking out random calls with no
[00:06:19] Leah Tillyer: no kind of strategy behind it, just hoping to to pick a couple of variations, to give some good feedback and make sure compliance. Elements are being carried out, and then the call sampling is often limited as well. So some clients that we speak to will do a couple of calls per agent per month, and others
[00:06:41] Leah Tillyer: a couple of calls per agent per quarter. They just don’t have the man hours or the resource that they need. And it’s a really time consuming task. They’re taking extensive notes throughout. So I’m sure that resonates with a few people. And then on the flip side of that where where contact centers or teams have a speech analytics software already.
[00:07:06] Leah Tillyer: it’s not a new technology. It’s been around for between 10 and 15 years now. So if they’ve had it for a while. It’s often clunky and cumbersome. It can be inaccurate because it relies on
[00:07:19] Leah Tillyer: the manual input of data and the manual tagging of data. The technology behind speech. Analytics now has come a long way with the introduction of AI. But if you’re using a legacy platform or product, it can be a time consuming process. They’re often really complicated and complex to set up. And
[00:07:43] Leah Tillyer: with that comes a lot of
[00:07:46] Leah Tillyer: time consuming maintenance to keep it up to date and relevant as well.
[00:07:50] Leah Tillyer: and sync delays are a big issue. We speak to customers where their previous platforms would sync twice a week, and and of course, in terms of the information that they need to get back. People want that within the within 24 h, or as near to real time as possible. And then this siloed data across the contact center. It’s usually a separate system. It doesn’t integrate with their call software. And
[00:08:19] Leah Tillyer: so because of those reasons.
[00:08:21] Leah Tillyer: contact centres, sales and customer service and debt collection teams are missing out on really valuable insights. They’re not seeing the whole picture across the contact centre. They’re seeing a really small part of it, and the process behind it is
[00:08:39] Leah Tillyer: It’s clunky. It takes time. It’s not something that’s prioritized as a business.
[00:08:47] Leah Tillyer: We last year as a as a company, carried out an independent benchmark survey of over 500 Contact Center leaders in the sales and collections and customer service space and we were looking at metrics
[00:09:04] Leah Tillyer: to track across those areas and how they drive successful outcomes for businesses. So looking at sales performance today? And how do you compare? How does your sales team compare? And how do you start to deliver and drive results?
[00:09:22] Leah Tillyer: And some of the things that we were seeing across different contact centres was, I’m sure we’re already aware of this. But sales is a numbers game. So the report showed that teams made up that made more calls tended to achieve greater success. So the average number of calls from this report was around 65 per agent, which is
[00:09:46] Leah Tillyer: a really big number of calls to hit. And it’s where your automated dialling technology comes in. And obviously, the more calls you’re making and the more strategic you are with those calls as well with with
[00:09:59] Leah Tillyer: skills, matching, and things like that. The higher the success rate is. And then we looked at
[00:10:05] Leah Tillyer: 1st call close rate as well. So the higher that your 1st call close rate, it typically shows how well your team are trained and qualified to convert. So a low call, close rate. It might indicate a lack of empathy on a call or a poor understanding of the product or the service that they’re selling or not understanding or able to convey their value. Proposition.
[00:10:29] Leah Tillyer: So average 1st call close rate was around 28% across the contact centres that we surveyed.
[00:10:40] Leah Tillyer: and then just looking at conversion rates as well. And across those so average conversion rates for campaigns is around 7%. And that’s
[00:10:52] Leah Tillyer: that’s within the I guess, above average range with around 26% of contact centres falling into that good range of between 4 and 5%.
[00:11:04] Leah Tillyer: So just some nice benchmark stats to be looking at there around performance of your sales team within the contact centre, and what they’re coming up against.
[00:11:15] Leah Tillyer: And we also looked at some roi stats as well. So how much revenue is generated per agent per successful call, and and this was looking at nearly 200 pounds per agent per successful call. So really giving you an understanding of the Roi per campaign or team or user.
[00:11:40] Leah Tillyer: I think it’s important to have a view of how other contact centres are performing. But also looking at how you benchmark against yourself in these metrics. And as you start to look at introducing dial in technology or using dial in technology and improving it. With different tactical approaches, with the campaigns. Introducing things like speech analytics. How you then improve. Your own benchmarks
[00:12:10] Leah Tillyer: and tracking is, I think.
[00:12:15] Leah Tillyer: and understanding performance is half of the picture. But I think the future of sales success. It really lies in smarter listening. And so that’s something that we’re going to talk about a little bit more now, with Connor. So I’m going to
[00:12:39] Leah Tillyer: Pass over to Connor to share his screen.
[00:12:44] Leah Tillyer: we’re going to go off camera for this now, just so you can concentrate on what is being shared.
[00:12:56] Conor Bowler: All right. So, as Leah said, the future of sales, success is smarter listening.
[00:13:01] Conor Bowler: So it’s all about turning every conversation you have into competitive edge
[00:13:06] Conor Bowler: customer experience. Obviously about the 3 S’s success, sentiment, and satisfaction
[00:13:11] Conor Bowler: with your traditional CCaaS analytics. You’re only going to get the 1st 3 of these with spoken. You’ve got all 3 the full picture.
[00:13:20] Conor Bowler: So we’re focused on success intelligence today to track agent performance and providing coaching insights. So you’re seeing their true behaviors, habits, and trends.
[00:13:29] Conor Bowler: But let’s start with improving visibility into AI insights to call sentiment for agents. So you want to get a consistent objective view of customer emotions across every single call.
[00:13:40] Conor Bowler: Not just a few. You Qa. Manually.
[00:13:43] Conor Bowler: What happens to cinnamon when you make some changes to a script are running some training
[00:13:49] Conor Bowler: onboarding a new agent.
[00:13:52] Conor Bowler: So at Spokn AI you have a whole set of charts to do this.
[00:13:55] Conor Bowler: Let me show you so. If I take a look at last month. Yeah, I can see that there’s been some small shifts. So we’ve gone from 73% to 74% positive sentiment.
[00:14:06] Conor Bowler: But equally, we’ve gone from 8% negative sentiment to 9%, a small hop up
[00:14:12] Conor Bowler: and let’s like, kind of look down and drill into it and see if we can kind of understand.
[00:14:18] Conor Bowler: So if I kind of come down the bottom here, we have lots of different charts
[00:14:23] Conor Bowler: and tables to help you kind of understand why that’s happening. If we keep this conversation focused on like agent performance and coaching.
[00:14:31] Conor Bowler: then, instead of looking at campaigns, I might look at users.
[00:14:35] Conor Bowler: so is there a lack of empathy or emotional intelligence for some of my agents? Can I coach them on building a better rapport.
[00:14:44] Conor Bowler: maybe, Andre here. He’s pretty high
[00:14:47] Conor Bowler: as I scroll down through them.
[00:14:50] Conor Bowler: You can see that there are others in that same kind of boat. So we have Eric here. And Estelle.
[00:14:56] Conor Bowler: Okay, I also have all of the different topics that are discussed on the call
[00:15:01] Conor Bowler: and the kind of level of sentiment towards each of these. If the sample size that I’m looking at is too large, then I can drill down even further.
[00:15:11] Conor Bowler: All right. So let me go back up here. My sample size currently is 7,630. We’ll look at how we filter.
[00:15:20] Conor Bowler: We have like really broad and kind of powerful filters. So I can filter down by perhaps an individual campaign. If that’s what I’m interested in
[00:15:29] Conor Bowler: by list or data supplier to see if it’s a data quality issue that’s leading to this kind of like negative sentiment.
[00:15:35] Conor Bowler: I can have a look at the Peak sentiment or the end sentiment on the calls. So what’s happening at the most intense parts of the calls. And what’s happening at the end of the calls, which are the ones that kind of truly affect those 3 s’s of like customer experience.
[00:15:51] Conor Bowler: But in this case let’s filter down by topic.
[00:15:57] Conor Bowler: So all was discussed on the call.
[00:16:00] Conor Bowler: So if I hit in disputes here, and I apply that filter
[00:16:07] Conor Bowler: unsurprisingly, you’ll see the negative sentiment hop right up there.
[00:16:12] Conor Bowler: Okay, now that I’ve got my calls. So I have like 332. Now, instead of my 7,000 and odd, some kind of a manageable number.
[00:16:22] Conor Bowler: I can go in to look at them so I can click on this playback page. Here I can see all the different interactions that supported. I can look through the summaries of those calls.
[00:16:33] Conor Bowler: and there are kind of overall view of sentiment, the transcripts, the sentiments in there, too, kind of any objections that came up in the call, the history of the call. Everything. Okay, I can even kind of drop down into the recording itself and understand where the different pieces of sentiment were and where the objections were in the different parts of the call, so I can go straight to those. I can play it at like double speed and everything to make sure that we’re getting it like
[00:17:01] Conor Bowler: done quickly.
[00:17:03] Conor Bowler: So you want all of this because well, customer experience is emotional, isn’t it? It’s about how how customers feel during those interactions
[00:17:12] Conor Bowler: to give you that sentiment and satisfaction that you’re combining with your Ccas analytics to give you success.
[00:17:18] Conor Bowler: retention, and loyalty are obviously tied to emotion. So negative sentiment, especially when you don’t notice it leads to churn poor reviews, damage, brand trust.
[00:17:29] Conor Bowler: and agents need this kind of feedback. So without visibility, agents don’t know when they’re succeeding emotionally or falling short.
[00:17:37] Conor Bowler: Okay, now, let’s navigate here to our Success Intelligence Page, and look at some of these additional tools
[00:17:48] Conor Bowler: that allow you to kind of track the performance and provide coaching insights.
[00:17:55] Conor Bowler: So here we have kind of call etiquette statistics.
[00:18:00] Conor Bowler: So we can look at longest monologue or longest silence to figure out if the talk to listen. Ratio
[00:18:07] Conor Bowler: isn’t right across a campaign, a team or a user.
[00:18:10] Conor Bowler: Okay, we’re looking at users right now as that’s where we’re focused.
[00:18:16] Conor Bowler: I have these stats for all of the individual users. They are combined with their conversion rates. There’s a number of successes that they’re having the successes per hour, all of that. So you can kind of begin to judge them holistically.
[00:18:30] Conor Bowler: Okay, equally, I can have a look at their objections.
[00:18:36] Conor Bowler: So we’re going to look at their objections so that they can turn more, maybe Laters into yes, nows like consistently.
[00:18:45] Conor Bowler: So here we can see the different objection categories that are trending.
[00:18:49] Conor Bowler: How is the coaching that we’re going to deliver, affecting what is here affecting the trending of the objections?
[00:18:57] Conor Bowler: So we have all of the objections into categories. They’re in need, time, trust, and cost.
[00:19:04] Conor Bowler: But equally we can drill down by individual reasons. So maybe I am, and kind of tick them on and off. So maybe I just want to see the trend and not interested
[00:19:18] Conor Bowler: here. We go over that period of time.
[00:19:21] Conor Bowler: and we’re really kind of measuring. What matters. So by tracking that objection, frequency, the resolution success rates alongside, the sentiment shifts. We looked at earlier.
[00:19:31] Conor Bowler: We tie that frontline kind of conversations directly into business outcomes.
Conor Bowler: So we can analyze those objection patterns, and what we’ll do with them is refine our messaging our offers scripts so that fewer objections come up. In the 1st place.
[00:19:52] Conor Bowler: beneath it there’s a table of all the objections. And again, it’s kind of
[00:19:56] Conor Bowler: categorised by into the various different categories of need, trust, cost, etc.
[00:20:02] Conor Bowler: But also kind of has it alongside conversion rate, some success statistics. And then you have the effectiveness, and that’s the key one here. The effectiveness is, how how many times that agent handled that objection successfully or not.
[00:20:22] Conor Bowler: So if we drill through.
[00:20:27] Conor Bowler: So I can see that trending in a kind of breakdown of handling effectiveness.
[00:20:33] Conor Bowler: So here’s my kind of basic information. I’m not interested. Here’s the trending of it in it, the different weeks, but also down the bottom. Here are my different agents, and how effectively they’re handling that not interested objection.
[00:20:49] Conor Bowler: Okay.
[00:20:51] Conor Bowler: not only that, but I can go up here, and I can like click in, and it’ll just highlight my top and bottom performance in this kind of area.
[00:21:03] Conor Bowler: And I can drill through to see those various interactions.
[00:21:08] Conor Bowler: Okay, there’s only like 4 or 5 or 9 here. So I’m going to go back.
[00:21:14] Conor Bowler: And maybe what I want to do is drill through all of those different things.
[00:21:20] Conor Bowler: So I’m going to go to my filters again. I’m going to add my objection of not interested.
[00:21:32] Conor Bowler: Apply those filters and have a look at the calls.
[00:21:38] Conor Bowler: Okay, so here are all calls where the objection not interested has come up.
[00:21:46] Conor Bowler: and I can go through those like my sentiment calls individually.
[00:21:50] Conor Bowler: and look through those kind of summaries, transcripts, histories to kind of figure out what’s going on. But equally I might do something a little smarter.
[00:22:00] Conor Bowler: and I find it really interesting to understand the calls that are not interested, but whereby there was some buying signals on them. So let me add a filter here, and we have all of these kind of search and transcript filters.
[00:22:14] Conor Bowler: so I could add some kind of buying criteria that I’m looking for. So if it maybe contains
[00:22:23] Conor Bowler: how much is it that’s kind of a buying signal. If the customer is talking about payment plans, another buying signal, and really, we want to. If any of these come up. So instead of the Ands, I’m going to turn this to an or how soon could I get it? Is it in stock right now? Can I pick it up today? All buying signals?
[00:22:44] Conor Bowler: I’ll just talk to my partner.
[00:22:48] Conor Bowler: It’s another good one, or I just need to check my budget and be helpful. If I could sell.
[00:22:56] Conor Bowler: I can add individual groups within these
[00:22:59] Conor Bowler: and continue to add those groups and make them more complex or less complex. Okay, so there’s
[00:23:05] Conor Bowler: it’s really kind of within your hands as to what you want to look at.
[00:23:09] Conor Bowler: I apply these filters.
[00:23:12] Conor Bowler: There we go. We have gone down from kind of our top things to just 40 items that so calls that have not interested objections that are
[00:23:24] Conor Bowler: that have buying signals within them.
[00:23:27] Conor Bowler: And I could even go and kind of say, well, it doesn’t really matter until unless it’s like not a successful call. So I can add that as a filter as well.
[00:23:38] Conor Bowler: Okay.
[00:23:42] Conor Bowler: not only that, but we make all of this information. So all of the call summaries, the transcripts, the sentiment, the objection handling, we make it available directly to individual agents within the contact hub, agent platform.
[00:23:56] Conor Bowler: And that’s so. The agents themselves can be more efficient, and they can look at themselves how to self-improve.
[00:24:03] Conor Bowler: But essentially all of these tools, mean, spoken helps coaching become more personalized and precise. So helping ages to improve faster without blanket training sessions, we can stop top, spot, even spot, top and bottom performance performers, track improvement over time and set goals with data. So not just instincts anymore
[00:24:25] Conor Bowler: providing this kind of feedback and allowing those agents to self serve on some of that feedback boosts employee engagement and reduces turnover.
[00:24:36] Conor Bowler: as a whole Spokn AI doesn’t just help you to listen to your customers. It helps you to understand them at scale, so it brings those hidden insights to the surface. It empowers your agents to perform at their best, and it gives your leadership the visibility needed to make faster and smarter decisions.
[00:24:54] Conor Bowler: All right, let’s go back to the main webinar.
[00:25:02] Leah Tillyer: Thank you, Conor, for running through that it was good to see in action, and just put some of
[00:25:11] Leah Tillyer: Some of those use cases to life around QA, and how it could be done differently, and how the coverage can be across everything, and then the insights that that can reveal. If anybody has any questions, now is the time to ask
[00:25:33] Leah Tillyer: Okay, we’ve got a question. How are you exploring? The debt collection use case. So we have clients across sales, debt collection and customer service. So that’s something we’ve not spoken about yet.
[00:25:48] Conor Bowler: Yeah, so I think the objections are really different, aren’t they? Cause they’re different use cases. So there are. The categories are much less kind of need and trust.
[00:25:59] Conor Bowler: But they’re more kind of can’t pay, won’t pay, and the variety of like different things underneath that we’re partnering with the Debt Collection Contact Center at the moment to build those out.
[00:26:10] Connor Bowler: And if I if I if anyone on the call like, wants to volunteer and and partner with us that’d be great as well.
[00:26:16] Connor Bowler: And we expect to have those done in the next few weeks.
[00:26:20] Leah Tillyer: Yeah, amazing. And you you showed the filters there as well. And the buying signals.
[00:26:27] Leah Tillyer: can you save the filters? What? What?
[00:26:30] Leah Tillyer: Yes, like? How complex can you get with them?
[00:26:34] Conor Bowler: Yeah, so those kind of transcript filters like you can write up to 250 or so different things, you know.
[00:26:41] Conor Bowler: and he can.
[00:26:42] Conor Bowler: and mix them with different logical operators, and or, as you can say, whether they have to be like bang on, whether they don’t contain things as an out of compliance whether they’re similar to or like
[00:26:57] Conor Bowler: And yeah, so like, if you’re writing those 250 different things you don’t wanna like, do it over and over again. So definitely, yeah, you can save those filters, click on it and then come back every day and and have a look at your miss buying signals for yesterday, or your competitor mentions for yesterday or your script. Adherence issues for yesterday, or you’re out of compliance. Calls for yesterday.
[00:27:18] Conor Bowler: Yeah.
[00:27:19] Leah Tillyer: Yeah.
[00:27:19] Leah Tillyer: Amazing
[00:27:21] Conor Bowler: Yeah.
[00:27:21] Leah Tillyer: Thank you. We have. We’ve got a couple more questions that have come in. So the 1st one can the analytics for spoken AI be downloaded into an excel spreadsheet
[00:27:34] Conor Bowler: Yeah, okay. So they
[00:27:39] Conor Bowler: there’s a like a download button on the top, right
[27:39] Conor Bowler: there’s a like a download button on the top, right? They can be like pulled out into PDFs.
[27:47] Conor Bowler: We’re looking to kind of like. Do some kind of chatbot integration as well.
[27:54] Conor Bowler: right now. No, they they can’t be pulled out into an Excel spreadsheet. You can pull them out into the PDF. And then take them from there into the Excel. But
[28:02] Conor Bowler: it’s a good. It’s a good shout and yeah, something we should definitely look at
[28:07] Leah Tillyer: Yeah, absolutely. Thank you. And then the next question is, how are the objection? Categories determined as a fundraising agency? We will have slightly different objections to normal contact centres.
[28:21] Conor Bowler: I think that’s similar to to the kind of 1st question around, you know, like there’s various different sales objections. And then there’s
[28:30] Conor Bowler: you know, the debt management type of stuff has different objections again.
[28:33] Conor Bowler: And yeah, if we’d love to work with you as a as a kind of charity or fundraising agency in order to be able to determine what those are and get that kind of training set.
[28:46] Conor Bowler: So
[28:47] Conor Bowler: we essentially like, take a lot of your calls. Initially, we like run through them. We find kind of open questions from there. We kind of put them through small language models, and we like, consolidate them to understand what the objections should look like. We feed them into spoken, and then they get pulled out as objections from there on
[29:07] Leah Tillyer: Yeah, I mean.
[29:08] Conor Bowler: So definitely, we can do that as well
[29:10] Leah Tillyer: Yeah, it was an anonymous question. So whoever reached out, if you we do, we run design partner programs. That’s something we do with all of our customers, and if there’s something we’re exploring, or there’s something new that we’re taking to market, we often work with a client on that, and what that looks like and start to build that out with real life, scenarios and data and information. So yeah, and please do get in touch off the back of the webinar. We’d love to see if we can work with you on that one.
[29:41] Leah Tillyer: I’m gonna say, final call for questions. There’s no more that popped up, but this is usually when they do pop up. I guess, whilst we’re waiting to see if any more come in just to to recap on some of the things that we have covered. So we’ve just understood a little bit more around. How? How contact centers, how sales collections and customer service are currently doing QA, and
[30:07] Leah Tillyer: how that can be evolved to give more insights to the contact center. We looked at some benchmark stats across sales, and how other businesses are doing it, and how they’re performing. And of course we’ve explored spoken, and the newest feature within that which is success, intelligence. If there are any existing spoken clients on the call
[30:31] Leah Tillyer: you should all have access to success. Intelligence now within the existing spoken package, and for any customers looking to explore, spoken as well, and for
[30:43] Leah Tillyer: for a limited amount of time we’re including spoken
[30:46] Leah Tillyer: within the base package as well. So it’s a good time to have the conversation.
[30:51] Leah Tillyer: And so there’s no more questions that have popped up. But yeah, thank you, everybody for your time. Thank you for Connor for running us through that, and we will share the recording afterwards as well
[31:05] Conor Bowler: Cheers! Folks take care!
[31:06] Leah Tillyer: Lovely bye, bye.
[31:07] Conor Bowler: Bye, bye.
Your Questions Answered
Adapting to Different Industries
Q: How are you exploring the debt collection use case?
Connor Bowler, Principal Product Manager: “The objections in debt collection are really different from standard sales objections. Rather than categories like ‘need’ and ‘trust,’ they’re more focused on ‘can’t pay’ versus ‘won’t pay,’ with various subcategories beneath those. We’re currently partnering with a debt collection contact centre to build out these specialised objection categories, and we expect to have those completed in the next few weeks. We’d welcome any volunteers from the call who’d like to partner with us on this initiative.”
Q: How are the objection categories determined for a fundraising agency? We will have slightly different objections to normal contact centres.
Connor Bowler: “This is similar to the first question about different sales objections versus debt management objections. We’d love to work with you as a charity or fundraising agency to determine what those specific objection categories should be and develop the appropriate training set. Our process involves taking a sample of your calls, running through them to identify common patterns, using small language models to consolidate these patterns, and then feeding them into Spoken to automatically detect these objections going forward.”
Leah Tillyer, Product Marketing Manager: “We run design partner programmes with all of our customers. When we’re exploring something new or taking it to market, we often work directly with a client to build it out with real-life scenarios, data, and information. We’d love to connect after the webinar to explore working together on this.”
Technical Capabilities
Q: Can the analytics for Spoken AI be downloaded into an Excel spreadsheet?
Connor Bowler: “There’s a download button in the top right that allows you to pull reports out as PDFs. Currently, you can’t export directly to Excel, but you can take the PDF and convert it to Excel. It’s a good suggestion and something we should definitely look at implementing. We’re also looking to integrate some chatbot functionality in the future.”
Q: Can you save the filters? How complex can you get with them?
Connor Bowler: “Yes, you can save filters, which is especially useful since our transcript filters allow you to include up to 250 different search terms. You can mix these with different logical operators like ‘and’ or ‘or,’ specify whether matches need to be exact, exclude certain phrases for compliance checks, or look for similar patterns. Once saved, you can click on a filter and reuse it day after day to check for missed buying signals, competitor mentions, script adherence issues, or compliance concerns from yesterday’s calls.”
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