10 Best Call Center Analytics Software for Sales and Support

Best Call Center Analytics Software for Sales and Support: Comparison Table

Compare the ten call center analytics tools in this guide on what each one is built for, what it costs to start, and how its own users rate it.

Why Do Sales and Support Teams Need Call Center Analytics Software?

According to McKinsey & Company's 2024 analysis of gen AI in customer care, manual call-evaluation methods typically cover less than 5% of total call volume¹.

Think about what that means on a floor doing 10,000 calls a month. Every coaching conversation and every escalation to product rests on a few hundred calls somebody had time to listen to. The objection that killed last quarter's biggest deal is sitting in the other 9,500, along with the billing confusion that keeps generating repeat contacts.

Most teams try to close that gap by adding a QA analyst or building a shared sheet of hand-scored calls. You get a slightly bigger sample and a much slower feedback loop, and the majority of your conversations still go unread.

Call center analytics software attacks the problem from the other end. Instead of sampling, it transcribes and scores every conversation, then rolls the results into dashboards a sales manager or support lead can act on the same week. That's the difference between spot-checking calls and running continuous call center analysis. We reviewed 10 of the best call center analytics tools for sales and support teams. You'll see what each one costs, which side of the house it suits, and where it runs out of road.

What Is the Best Call Center Analytics Software for Sales and Support in 2026?

For most sales and support teams, the best starting point is CloudTalk: dashboards, reporting, and AI insight on the same platform that places the calls, so both sides of the house are covered without a second vendor. The specialists still earn their places — for support QA at scale, Level AI and CallMiner lead on automated scoring depth, and for sales-call analysis tied to revenue, Gong is the reference point.

What Does Call Center Analytics Software Actually Do?

Call center analytics software collects data from phone conversations and the systems around them, then turns it into metrics, transcripts, and reports. It answers three kinds of questions:

What Are the Main Types of Call Center Analytics?

Call center analytics breaks into five types: interaction and speech analytics, voice and acoustic analytics, real-time analytics, predictive analytics, and text and omnichannel analytics. Vendors bundle them differently, which is why two products in the same category can look nothing alike in a demo.

How Is Call Center Analytics Different From Speech Analytics and Conversation Intelligence?

Call center analytics is the parent category, and speech analytics and conversation intelligence are two slices of it. The labels overlap, and vendors reach for whichever one is selling that year.

Contact center analytics software is the broadest term: operational metrics plus conversation content across channels. Call analytics software and speech analytics are narrower labels for the voice-only slice: mining audio and transcripts from phone conversations.

Conversation intelligence usually means speech analytics packaged for a specific team, with revenue intelligence being the sales-focused branch of it. That's why Gong and NiCE CXone can both appear on this list while solving almost nothing in common.

Salesforce's State of Service research, published in November 2025, found service teams estimate AI currently handles 30% of cases, and project that it will reach 50% by 2027². As that share grows, the analytics question shifts from "how did my agents do" to "how did my agents and my automation do together", and the tools that only read human calls will start to look partial.

Our Methodology: How We Reviewed These Call Center Analytics Providers

We built this list from vendor documentation, published pricing pages, and aggregated review themes on G2 and Trustpilot, then pressure-tested each tool against a working buyer's question: what does it tell a sales manager or a support lead on a Monday morning?

Four rules shaped the ranking. We verified every price at the vendor's own pricing page and said "quote-based" where no public price exists, instead of repeating a figure from another listicle. We treated Verint and Calabrio as one vendor, because they're one company now. CloudTalk leads the list because it's the one tool here where the analytics and the calls come from the same vendor — and because it's ours, which is why every entry below still names the tools that out-depth it. Where a tool has a real weakness in its review base, it appears in the entry.

The 10 Best Call Center Analytics Tools in 2026

1. CloudTalk

What Is CloudTalk?

CloudTalk is AI business calling software for growing SMBs: a cloud phone system built for sales and customer support teams, with call analytics and reporting shipped as part of the platform. Five of the ten tools on this list are analytics layers that sit on top of somebody else's telephony, and four are enterprise contact center suites. CloudTalk is the SMB and mid-market option where the analytics and the calls come from the same vendor.

That's a scope trade-off rather than a claim of parity. You get one vendor, one bill, and no integration project. What you don't get is the analyst-grade depth of CallMiner or Verint.

What Are CloudTalk's Key Features?

Pros and Cons of CloudTalk

What Is the Pricing of CloudTalk?

Add-on available:

When Should You Use CloudTalk (And When Shouldn't You)?

Use CloudTalk if you're an SMB or mid-market sales or support team (or both) that wants one vendor, one bill, and no integration project. Dashboards, historical reporting, and, with the AI add-on, transcripts, sentiment, topics, and AI call scoring all sit on the same platform that places the calls. It's a particularly good fit if you also need outbound dialing, since campaign analytics and Conversation Intelligence output land in the same place.

Skip CloudTalk if you need enterprise-grade speech analytics with a dedicated analyst team, which is Verint and CallMiner territory. Also skip it if you need transcription or sentiment during the live call, where Dialpad is stronger, or if you want to keep your existing telephony and add only an analytics layer on top.

What Do CloudTalk Customers Say?

Routing and queue control dominate the positive G2 themes, usually paired with CRM sync keeping call data attached to the right record. Trustpilot reviewers tend to talk about the basics working: clear call quality, a stable platform, and onboarding that doesn't need a consultant. The critical reviews cluster around commercial friction rather than the product, with account activation, billing disputes, and unclear upgrade paths appearing more than once.

G2 rating: 4.4/5 (1758+ reviews) · Trustpilot: 4/5 from 380+ reviews

2. Level AI

What Is Level AI?

Level AI describes itself as "a customer intelligence platform that analyzes the intents and meanings expressed by customers and agents in all contact and call center interactions." It's an analytics layer, not a phone system, and it's built for support and blended teams whose QA process has become the bottleneck.

What Are Level AI's Key Features?

Pros and Cons of Level AI

What Is the Pricing of Level AI?

When Should You Use Level AI (And When Shouldn't You)?

Use Level AI if you run a support or blended team, call center quality assurance is your bottleneck, and you're happy with the telephony you already have. Level AI adds analysis on top; it doesn't replace the phone system.

Skip Level AI if you need a phone system as well, you want a published price before a sales call, or transcription accuracy in a non-English-dominant environment is critical to you.

What Do Level AI Customers Say?

G2's aggregated themes lead with ease of use: an intuitive interface for reviewing customer interactions, and 81% of the 199 reviews sitting at five stars. The most common complaint is accuracy: sentiment and transcription results that need a human check. Reviewers running global accounts also flag that getting data out of the platform takes more manual work than they expected.

G2 rating: 4.7/5 (199 reviews)

3. Observe.AI

What Is Observe.AI?

Observe.AI positions itself as an AI-native conversation intelligence platform for contact centers, pairing real-time agent assist with automated QA on every interaction. It shows up most often in regulated environments, where compliance monitoring is part of the buying requirement, not a nice-to-have.

What Are Observe.AI's Key Features?

Pros and Cons of Observe.AI

What Is the Pricing of Observe.AI?

When Should You Use Observe.AI (And When Shouldn't You)?

Use Observe.AI when compliance is a hard requirement, your call volume is large enough that sampling is indefensible, and you want live assist as well as post-call analysis.

Skip Observe.AI if you're under roughly 50 agents, since the pricing model and implementation overhead don't amortize well at that size, or if you need accurate transcription in languages outside the core set.

What Do Observe.AI Customers Say?

The pattern in G2's aggregated themes is consistency: reviewers like that scoring no longer depends on which supervisor happened to listen. Real-time coaching shows up as a strength in its own right, separate from the post-call QA story. Against that, transcription and sentiment accuracy come up repeatedly, and reviewers describe onboarding as a project that needs Observe.AI's team involved.

G2 rating: 4.6/5 (249 reviews)

4. CallMiner

What Is CallMiner?

CallMiner, whose flagship product is CallMiner Eureka, is an enterprise conversation intelligence platform. It analyzes conversations across voice, chat, email, and social for sentiment, compliance risk, topics, behavioral patterns, and CX trends, and it's built for organizations with a dedicated analytics function.

What Are CallMiner's Key Features?

Pros and Cons of CallMiner

What Is the Pricing of CallMiner?

When Should You Use CallMiner (And When Shouldn't You)?

Use CallMiner if you have a dedicated analytics or quality assurance analyst function, high interaction volume, and compliance or fraud exposure that justifies specialist depth. Few tools go deeper.

Skip CallMiner if you have nobody to run it day to day, you need measurable value inside a quarter, or you want a price before a procurement cycle starts.

What Do CallMiner Customers Say?

The strongest theme is scale: G2 reviewers report a dramatic increase in the volume of interactions they can audit in the same amount of time. Reviewers also credit the vendor with responsiveness on feature requests. The counterweight is effort, with training time, filter-heavy interfaces, and slow large exports all recurring. Cost appears as an internal-politics problem more than a value problem.

G2 rating: 4.5/5 (235 reviews)

5. Dialpad

What Is Dialpad?

Dialpad calls itself "one platform for every conversation, workflow, and channel", an AI-powered customer communications platform spanning AI Agents, Support, Sell, and Connect. Its distinguishing claim in this category is timing: analysis while the call is happening, not after it ends.

What Are Dialpad's Key Features?

Pros and Cons of Dialpad

What Is the Pricing of Dialpad?

When Should You Use Dialpad (And When Shouldn't You)?

Use Dialpad when live coaching and in-call intelligence are the whole point, and you want supervisors intervening during the call instead of reviewing it tomorrow.

Skip Dialpad if what you want is a deep historical analytics warehouse rather than real-time signals.

What Do Dialpad Customers Say?

Reviewers consistently like the consolidation: calls, messages, and support in one place, with summaries and transcripts attached. The real-time AI gets credit for working as advertised. The friction shows up after the sale, in implementation coverage and in support quality on complicated issues.

G2 rating: 4.4/5 (4,800+ reviews) · Trustpilot: 4.1/5 from 2,900+ reviews

6. Gong

What Is Gong?

Gong is a revenue intelligence platform. It captures and analyzes customer interactions to give revenue teams visibility into deals, pipeline, and rep performance, which makes it the sales-side specialist on this list, not a contact center tool.

What Are Gong's Key Features?

Pros and Cons of Gong

What Is the Pricing of Gong?

When Should You Use Gong (And When Shouldn't You)?

Use Gong when your analytics question is "why are we winning and losing deals, and which rep behaviours change that", and you have budget for a platform fee on top of licences.

Skip Gong if you need support or contact center operational analytics, if you're price-sensitive, or if your volume is inbound service instead of sales conversations.

What Do Gong Customers Say?

Gong has the strongest review profile of any tool here, with roughly 88% of its G2 reviews at five stars. Depth on sales-conversation analysis is the theme its reviewers keep coming back to. Price is the recurring counterpoint, and scope is the second one: Gong was never built to cover support QA, so AHT, queue, and FCR analytics aren't there.

G2 rating: 4.7/5 (6,600+ reviews)

7. Verint (Including Calabrio ONE)

What Is Verint?

Verint is a customer experience (CX) automation and workforce engagement platform, currently framed around its Open Platform, Agent Factory, Da Vinci AI, and CX Data Hub. One thing worth knowing before you shortlist: Verint and Calabrio are now one company under the single Verint name, following Thoma Bravo's take-private of Verint in January 2026 and the combined organization's announcement in February 2026. Calabrio ONE continues as a platform within Verint, and calabrio.com now redirects to Verint's workforce engagement pages.

What Are Verint's Key Features?

Pros and Cons of Verint

What Is the Pricing of Verint?

When Should You Use Verint (And When Shouldn't You)?

Use Verint if you're an enterprise support organization that needs workforce engagement and interaction analytics from one vendor, and you have the implementation capacity for an enterprise deployment.

Skip Verint if you're SMB or mid-market, you need to be live this quarter, or you want roadmap certainty while a post-merger consolidation is still in progress.

What Do Verint Customers Say?

On the analytics side, reviewers value emotion detection and keyword spotting for spotting risk early, and rate the reporting depth highly. On the Calabrio ONE side, forecasting and scheduling accuracy are the standout themes. The consistent criticisms are the learning curve, transcription accuracy, and performance on large datasets. Reviewers of both products describe getting started as the hardest part.

G2 rating: 4.4/5 for Verint, with Calabrio ONE rated 4.5/5 from 394 reviews

8. Talkdesk

What Is Talkdesk?

Talkdesk is an AI-powered cloud contact center platform sold in per-seat editions across digital and voice engagement, with industry-specific Experience Clouds on top. Among the enterprise-leaning options here, it's the one that publishes what it costs.

What Are Talkdesk's Key Features?

Pros and Cons of Talkdesk

What Is the Pricing of Talkdesk?

When Should You Use Talkdesk (And When Shouldn't You)?

Use Talkdesk when you want a full contact center platform with analytics included and a price you can budget from a public page, and when vertical compliance features matter.

Skip Talkdesk if you only need an analytics layer on telephony you already have, or if your budget can't reach the tier where custom reporting unlocks.

What Do Talkdesk Customers Say?

G2 reviewers describe an interface their agents pick up quickly and AI features that reduce channel-switching. Publishing prices earns Talkdesk goodwill during evaluation. What the reviews don't soften is the tiering: Custom Reporting with Live and Explore starts at $165/user/month, roughly double Digital Essentials.

G2 rating: 4.4/5 (2,450+ reviews)

9. Five9

What Is Five9?

Five9 sells the Five9 Intelligent Cloud Contact Center Platform in channel-and-AI tiers, positioned around measurable CX outcomes. It appeared on more of the ranking pages we analyzed than any other vendor, usually as the recommendation for high-volume outbound.

What Are Five9's Key Features?

Pros and Cons of Five9

What Is the Pricing of Five9?

When Should You Use Five9 (And When Shouldn't You)?

Use Five9 for high-volume, omnichannel, enterprise operations where outbound scale and analyst-recognized reliability outweigh cost and review sentiment.

Skip Five9 on SMB or mid-market budgets, or when your analytics needs can be met without migrating your whole contact center.

What Do Five9 Customers Say?

Five9's enterprise track record and analyst recognition carry real weight in procurement, and the AI feature set is broad. Its G2 average is still the lowest of these ten at 4.1/5, and the documented friction is interface performance and slow exports of large reports, not missing capability. One more thing to price in: the tiers that add advanced AI and workforce engagement are the ones without a published number.

G2 rating: 4.1/5 (607+ reviews) · Trustpilot: 3.6/5 from 700+ reviews

10. NiCE CXone Mpower

What Is NiCE CXone Mpower?

NiCE positions CXone Mpower as an end-to-end, CX-aware AI platform for customer service, spanning agentic experience automation, a unified agent workspace, and workforce engagement. It's the category's largest incumbent and has the broadest analytics surface of anything on this list.

What Are NiCE CXone Mpower's Key Features?

Pros and Cons of NiCE CXone Mpower

What Is the Pricing of NiCE CXone Mpower?

When Should You Use NiCE CXone Mpower (And When Shouldn't You)?

Use NiCE CXone Mpower if you're a large omnichannel operation, analytics and workforce engagement depth is the deciding factor, and you have the budget and the implementation capacity for an enterprise platform.

Skip NiCE CXone Mpower if you're SMB or mid-market, you need fast time to value, or you can't justify $110 to $249 per agent per month against the analytics you'd use.

What Do NiCE CXone Mpower Customers Say?

Reporting is the headline strength in G2's themes, with reviewers singling out how quickly they can locate and pull specific calls. Stability gets consistent credit at scale. The complaints are about ergonomics and effort: extra clicks for routine actions, lag when switching between features, and reporting customization that G2 reviewers still want more of despite the depth.

G2 rating: 4.3/5 (1,700+ reviews)

How to Choose the Right Call Center Analytics Software

Deloitte Digital's 2026 service survey found 64% of service leaders reporting higher agent productivity and 39% reporting lower cost per contact as a result of AI⁴. Those outcomes aren't evenly distributed, and the difference usually comes down to buying decisions made months earlier. Six questions separate the teams that get value from the teams that get dashboards.

Sales Analytics vs. Support Analytics: What Actually Changes?

The metrics barely overlap, so a tool that's excellent for one side can be useless for the other.

On the sales side you care about talk and listen ratio, connect and conversion rates, objection and competitor mentions, and how conversation behaviour maps to pipeline. That's the raw material for using call analytics in sales reviews, and the reason call data usually has to sit next to the CRM and whatever sales email software your reps work out of. On the support side you're buying customer service analytics software, so you care about AHT, first-call resolution, CSAT, queue and abandon rates, QA scoring coverage, and contact-driver analysis that tells you why people called at all.

If you buy for both, check that the platform can separate them instead of averaging them. CloudTalk's Call Type Analytics Filter, for instance, splits Conversation Intelligence configuration between support and sales so the two reporting sets stay distinct.

Should It Replace Your Phone System or Sit on Top of It?

An analytics layer keeps your existing telephony and reads its audio; a phone system with analytics built in replaces the telephony too. This is the biggest structural fork in the category, and it's easy to miss because every vendor answers a different question well.

Five of the tools here are pure analytics layers: Level AI, Observe.AI, CallMiner, Gong, and Verint. Each assumes you keep your telephony and give it access to the audio, which is right if your phone system works and you only have an insight problem. It also means a second vendor, a second bill, and an integration to maintain. If you're replacing the phone system anyway, or you're small enough that a two-vendor stack is real overhead, a platform where the analytics ship with the calling is a simpler buy. And if reporting depth is the whole gap, something from our roundup of the best call reporting software may already cover it.

How Much of Your Call Volume Will Get Analyzed?

Every vendor says "100% of interactions", and most can technically deliver it. The practical limit is language coverage, the accuracy of the call transcription software underneath it on your accents, and whether your team trusts the output enough to act on it. McKinsey & Company's 2024 analysis of automated quality assurance estimates that a largely automated QA process reaches more than 90% accuracy, against 70% to 80% for manual scoring, while cutting QA costs by more than half. Ask for accuracy figures in your languages, not in general.

Do You Need Real-Time or Post-Call Insight?

Post-call analysis covers coaching, trend detection, and QA, which is most of the value most teams get. Real-time analysis covers supervisor intervention and live agent assist, and it costs more to build, which is why fewer tools do it well. Dialpad and Observe.AI are the strongest real-time options here. CloudTalk's Real-Time Analytics covers live queue, availability, and agent activity from the Essential plan, while its transcription and sentiment run post-call. For most supervisors, a live call center wallboard covers the in-the-moment job; live transcription is a much smaller club.

Who Will Run It After the Launch Project Ends?

The hard part starts after go-live, when somebody has to own the reports. McKinsey & Company's 2025 analysis of millions of interactions across more than 30 organizations found that 50% to 60% of customer interactions remain transactional despite significant efforts to eliminate them. A finding like that only turns into action if somebody owns call center metrics, analytics, and reporting as part of their actual job.

CallMiner and Verint reward a dedicated analyst function and punish teams without one. If nobody has this in their job description, buy the tool your supervisors can operate unaided.

What Will It Really Cost Over Three Years?

Published prices are the smaller half of the question. Six of these ten providers don't publish pricing at all, Gong adds a platform fee on top of licences, Talkdesk puts custom reporting two tiers above entry, and NiCE adds per-session charges on its top suite. Add-ons matter too: CloudTalk's AI Conversation Intelligence is $9/user/month on top of any plan, never included in one.

Our guide to how much call center software costs walks through the line items that usually show up after the quote.

Then weigh it against the upside. McKinsey & Company's 2024 quality-assurance analysis estimates gen AI in the contact center can deliver more than 50% savings in QA costs, a 25% to 30% increase in agent efficiency, and a 5% to 10% improvement in customer satisfaction. Those are the numbers to build your business case on, and they're also the numbers to hold the vendor to at renewal.

CloudTalk pricing starts at $25/user/month with historical reporting on the baseline plan. See all plans.

Quick Answers to Common Questions

What Are the Most Important Contact Center Analytics Metrics?

The most important contact center analytics metrics differ by team, and you want a list short enough to review every week. For support: average handle time, first-call resolution, abandon rate, CSAT, and QA score coverage. For sales: connect rate, conversion rate, talk and listen ratio, and objection frequency. Then add one diagnostic layer, usually contact drivers or topic trends, so you can see why the operational numbers moved. Our rundown of the most important call center KPIs is a reasonable starting shortlist.

How Does AI Improve Contact Center Analytics?

AI removes the sampling limit. Instead of a supervisor scoring a handful of calls, AI call center software transcribes and scores everything, and topic detection surfaces patterns nobody thought to look for. Deloitte Digital's 2026 service-maturity findings show 48% of companies with mature service capabilities already use agentic AI, double the 24% rate among low-maturity peers. The catch is accuracy: AI output still needs auditing against human scoring before you coach or discipline on it.

What Is the Difference Between Speech Analytics and Interaction Analytics?

Speech analytics works on voice: transcription, keyword spotting, tone, silence, and talk-over. Interaction analytics is the wider discipline, applying the same analysis to voice plus chat, email, tickets, and social, so a customer who called and then emailed shows up as one story. Vendors often sell the combined version as conversational analytics. If your volume is voice-only, speech analytics is enough. If customers reach you on four channels, interaction analytics is what stops you optimizing one channel while another degrades.

Why Do Many Call Center Analytics Implementations Fail?

Most call center analytics implementations fail for reasons that have nothing to do with the software. The data lands in a dashboard nobody owns, the QA rubric was never agreed, or the insight has no route into a coaching change or a call routing change. Deloitte Digital's 2026 Future of Service research reports that 43% of surveyed organizations believe AI will let them cut contact center costs by 30% or more within three years. The teams that get there decided in advance which decisions the analytics would change.

Can a Small Support Team Justify Call Center Analytics Software?

Yes, but not the enterprise kind. Below roughly 20 agents, quote-based platforms with implementation projects rarely pay back, while dashboards and historical reporting bundled into your small business call center software usually do. CloudTalk's Historical Reports and Analytics, covering call volume, agent performance, first-call resolution, and AHT with unlimited storage, are included from the Starter plan at $25/user/month, which is a very different commitment from a six-figure enterprise deal.

What People Say About Call Center Analytics Software on Reddit

Vendor review platforms tell you what buyers will say in public. Reddit and Quora tell you what they say to peers once the contract is signed, which is where the honest notes on transcription accuracy, hidden add-on costs, and abandoned implementations tend to live. It's the layer of evidence no vendor page and no call center software buyer's guide will hand you.

Reddit discussion:

Top Call Center Analytics Software by G2 Reviews and Ratings

Ratings are only meaningful next to volume, since 4.7/5 from 199 reviews and 4.4/5 from 1758+ reviews describe different levels of evidence. The table below covers the providers where CloudTalk, whose own call center analytics and reporting ships with the phone system, holds an edge on rating, review volume, or both. Gong, Dialpad, and Talkdesk are left out because CloudTalk beats them on neither measure. Verint is out for a different reason: its review count is unconfirmed (see its entry), so there is no volume comparison to make.

The specialists rate higher and are reviewed less, which is what you'd expect from tools bought by small analytics teams. The platforms carry more reviews and more mixed sentiment, because everyone in the contact center uses them, not just the person who chose them.

Which Call Center Analytics Solution Should You Choose?

In McKinsey & Company's February 2026 survey of 440 customer care leaders, 40% of the most AI- and data-mature organizations reported significantly improved customer experience scores over the previous 12 months, against just 12% of laggards. The best contact center analytics solutions for a 500-seat operation look nothing like the right pick for a 12-person support desk. That is also why a general best call center software shortlist and an analytics shortlist rarely hold the same names. What separated the two groups in that research was scaled adoption, not tool selection: 67% of leaders had invested in foundational AI use cases at scale, compared with 16% of laggards. So weigh adoption as heavily as capability when you shortlist.

Best Call Center Analytics Software for Small Teams

Under about 20 agents, the analytics you'll open are dashboards, historical reports, and per-agent numbers, the call reporting software end of the category, and the integration tax on a specialist platform is hard to justify. CloudTalk includes the Dashboard, Historical Reports and Analytics, and Agent Reporting on Starter at $25/user/month, with Real-Time Analytics from Essential and the AI Conversation Intelligence add-on available when you want transcripts and scoring. Dialpad is worth a look if live coaching is the reason you're buying.

Best Call Center Analytics Software for Mid-Market Sales and Support Teams

At mid-market scale the answer depends on which side of the house is buying. Sales teams tying calls to pipeline should shortlist Gong, budget for the platform fee, and expect the call data to end up alongside whatever sales automation software already drives their sequences. Support teams whose QA process has broken should shortlist Level AI and Observe.AI. Teams buying for both, especially with outbound in the mix, get further with one platform: CloudTalk's Expert plan at $49/user/month adds Customizable Dashboards, Wallboards, and Agent Status, and includes Power Dialer.

Best Call Center Analytics Software for Enterprise Contact Centers

At enterprise volume the deciding factor is depth plus workforce management, and the shortlist narrows to CallMiner, Verint, NiCE CXone Mpower, and Five9. CallMiner goes deepest on speech and text mining, Verint pairs interaction analytics with the strongest workforce engagement story, NiCE has the broadest suite at the highest published cost, and Five9 leads on high-volume outbound. All four assume you have analysts to run them, an implementation team to launch them, and a call quality management process mature enough to use what they produce.

Sources:

1. McKinsey & Company
2. Salesforce
3. Forrester
4. Deloitte Digital