aheadCRM - Blog #Call CenteraheadCRM - Blog #Call Centerhttps://www.aheadcrm.co.nz/blogs/tag/Call-CenterTue, 22 Sep 2026 12:04:04 -0700http://zoho.com/sites/<![CDATA[The great CCaaS Meltdown: What It Means for Customers and CX]]>https://www.aheadcrm.co.nz/blogs/post/the-great-ccaas-meltdown-what-it-means-for-customers-and-cx

The past weeks showed quite some interesting activity on the mergers and acquisitions and the partnership frontiers. NiCE acquired the German conversational AI rock star Cognigy for $955M and a short time later announced that the company enhanced its partnership with Salesforce. At nearly the same time, Genesys received an additional funding of $1.5 bn from Salesforce and ServiceNow. Salesforce acquired Waii and Bluebird. VC company Thoma Bravo acquired the still leading CCaaS vendor Verint, to name but a few of the more interesting, and perhaps consequential ones.

On top of all this, Avaya seems to have offered all employees a voluntary exit package.

What all this shows is that there is significant consolidation going on in the AI-assisted (or should I say, driven?) CCaaS market and that various players are battling to provide – or at least be perceived to provide – the most comprehensive and valuable platform while others fight for survival.

Yes, it’s nothing new, but can’t be repeated often enough. The CX market is and always was a high stakes platform game. The stakes got even higher with the advent, the promise and the necessary investments that generative AI and agentic AI require. While one can consider Salesforce’s acquisitions as tuck-ins that help rounding off its Agentforce platform, the other ones are a sign of something bigger going on in the CCaaS and customer service market segments. It is also notable that exactly these sectors get more and more referred to as CX market, whether this is a correct, or only good, attribution, or not. Hint: It isn’t.

Not unexpectedly, Salesforce is in the thick of all this, having a massive stake in Genesys and a strategic – at least for NiCE – partnership with NiCE. And regardless, of whether NiCE or Genesys turn out to be stronger, Salesforce wins.

For customers of the Salesforce ecosystem this, first of all, gives choice. For Salesforce, it gives access to a wide array of different customers and therefore the ability to fuel the data pipeline that Agentforce needs. With the different profiles of NiCE/Cognigy, customers need to establish for themselves whether they need the strengths on the customer service center side (NiCE/Cognigy) or the analytics and orchestration side (Genesys).

On the other hand, we have Verint getting into the fold of Thoma Bravo and being merged with WEM vendor Calabrio. This instantly creates a strong player that includes WEM and analytics capabilities. But looking into the Thoma Bravo portfolio, there is more, in particular Medallia. Adding Medallia’s capabilities adds improved journey management and especially a strong voice of the customer element that helps understanding and therefore improving customer sentiments at every single touch point. This would challenge CCaaS leaders like Genesys and NiCE by creating a comprehensive analytics story and a journey orchestration capability. With the help of UserTesting this gets even more pronounced as UserTesting’s technology allows the finding of a root cause of a problem identified using the Verint/Calabrio/Medallia stack. This combination can create something that one could call a total engagement and analytics platform that covers the capabilities of traditional customer service vendors, CCaaS vendors, and journey orchestration vendors. This has the potential to create a tectonic shift in these software categories, as they converge to form a kind of Gondwana of service solutions.

While this doesn’t necessarily create an immediate threat to the Zendesks and Freshworks of this world, it may severely limit their ability to enter into more complicated, multi-step service scenarios. On the other hand, this combination of Thoma Bravo capabilities needs to prove its ability to scale down to avoid being disrupted from below by vendors that have their strength in high volume ticketing scenarios.

I do not know whether this is what Thoma Bravo has in mind, but the scenario is quite appealing to me.

My analysis and point of view

But in any case, one thing is clear: The markets for conversational/agentic AI, CCaaS, UCaaS and customer service are converging while the markets are consolidating. And all of this seems to accelerate around two themes that NiCE and Genesys exemplify.

NiCE's is integrating vertically. The Cognigy acquisition is an integration move that aims at owning the full technology stack, from core CCaaS to best-in-class conversational AI. The goal is a seamless, single-vendor platform. The risks for customers are potential integration debt from the acquired asset, a less open and smaller ecosystem, and probably a premium licensing for these new capabilities after being locked in. The deepened Salesforce partnership is a pragmatic necessity to ensure relevance and access to the bigger ecosystem, not a fundamental strategy shift.

Genesys plays the ecosystem card. The capital injection from Salesforce and ServiceNow is probably a direct counter. It funds a horizontal integration strategy, betting that enterprises prefer a tightly integrated alliance of market leaders over a single-vendor suite, which is in line with both Salesforce’s and ServiceNow’s strategies. The risk is that these integrations remain shallow, and the "ecosystem" is more of a marketing concept than a technical reality. This largely depends on how the three parties build and execute their roadmaps.

Thoma Bravo’s portfolio around Verint can become a wildcard theme here. The merger of Verint and Calabrio would create a third force. This entity would not necessarily compete directly on the CCaaS infrastructure layer but would focus on the higher-margin levels, starting with WEM and interaction intelligence. Combined with the other portfolio companies, its power would come from either being a platform-agnostic integration hub—the "Switzerland of data" or becoming another vertically integrated solution.

With this convergence going on, customers will be able to create data informed and more seamless processes for their customers, simply because there will be deeper integration on a data platform level, not necessarily a software platform one.

What should customer executives look at now?

  • NiCE/Cognigy customers face significant integration risks due to two leading technologies being combined. Customers should demand a detailed, time-bound integration plan and roadmap with technical milestones. They need to have a deep and hard look at how their current licensing models are changed by new ones and model their TCO inclusive of probable premium "Cognigy-powered" features.
  • Genesys customers face a different execution risk. They require technical proof-of-concepts that demonstrate the depth and real-time nature of the Salesforce and ServiceNow integrations, respectively, along with a detailed integration roadmap. They should mandate that business value metrics be tied to the pricing and success of this "ecosystem."
  • Verint and Calabrio customers face a similar integration risk plus an uncertainty about the detailed positioning and future of Verint. Customers need to demand a detailed integration roadmap with milestones and clarity about the final strategy – platform neutrality or vertical integration.
  • Avaya customers are worst off – and have been for a while. Avaya is in survival mode. This situation requires immediate risk mitigation. Customers should work with a two-prongued strategy: Firstly, they need to secure existing SLAs and support commitments in writing. Secondly, they need to engage in a RFI/RFP process for at least two cloud-native CCaaS platforms. The objective is to have a fully vetted exit strategy that can be executed fast.

Some general recommendations

There is so much going on at a fast pace, that it pays off to reevaluate vendor roadmaps. An outdated understanding of your vendor's strategic position is a serious liability. The market of 18 months ago does no longer exist and the market of in 18 months will be very different from today’s.

As platforms consolidate, the risk of vendor lock-in increases. Customers should favor providers with a demonstrated commitment to an open, API-first architecture. There is no one-size-fits-it-all software platform for all businesses, nor will there be.

The current market will expose providers with weak financial fundamentals. Customers should review their vendor’s financial health and R&D investment as a default part of their due diligence.

Last, but not least, customers need to avoid AI-washing and require that any proposed AI solution be tied to a business case with measurable outcomes, such as reduced operational costs or improved containment rates. Additionally, contracts need to be tied to achieving these outcomes.

]]>Thu, 28 Aug 2025 17:56:37 -0400<![CDATA[Together, Zoom and Five9 shape a new market]]>https://www.aheadcrm.co.nz/blogs/post/together-zoom-and-five9-shape-a-new-market

The News

On July 18, 2021, Zoom Video Communications, Inc. announced the acquisition of Five9, Inc. in an all-shares transaction. The transaction values Five9 at around $14.7 billion.

According to the press release “the acquisition is expected to help enhance Zoom’s presence with enterprise customers and allow it to accelerate its long-term growth opportunity by adding the $24 billion contact center market.”

According to Eric S. Yuan, CEO and founder of Zoom, the company is “continuously looking for ways to enhance our platform, and the addition of Five9 is a natural fit that will deliver even more happiness and value to our customers”. He continues with “enterprises communicate with their customers primarily through the contact center, and we believe this acquisition creates a leading customer engagement platform that will help redefine how companies of all sizes connect with their customers”.

Rowan Trollope, CEO of Five9 adds that “businesses spend significant resources annually on their contact centers, but still struggle to deliver a seamless experience for their customers”. Trollope will become a president of Zoom and continue as CEO of Five9.

Zoom expects the acquisition of Five9 to be “complementary to the growing popularity of its Zoom Phone offering The combination of both firms also offers both companies significant cross-selling opportunities to each other’s respective customer bases”.

As especially Rowan Trollope emphasizes upon repeatedly in the acquisition briefing, this acquisition is about accelerating growth by combining the respective assets, software as well as customers.

The bigger picture

The trend towards call centers in the cloud has been there before and it has been amplified with the Covid pandemic. Connecting phone lines from diverse and independent locations into one telephony system gets greatly simplified with a cloud-based infrastructure and the required upfront investments are far lower.

At the same time, the desire and need for unifying personal as well as corporate communication have increased tremendously, for the same reason.

Last, but not least, it can be assumed that workforces will stay in a hybrid mode, with people having the ability to work from anywhere.

Zoom profited from the Covid pandemic in a phenomenal way and was probably one of the biggest winners. However, since October 2020, its stock price went down from a peak of nearly $560 to around $360 (July 22, 2021). This can be largely attributed to businesses having invested into communications tools and strong competition. Especially Microsoft has upped the ante considerably and invested heavily into its Teams software.

From an economy point of view, we are looking at the conversion of some markets in the ongoing platform game. We have the call center software landscape and the communications and collaboration software landscape – usually referred to Call Center as a Service and Unified Communications as a Service.

My Analysis and PoV

Zoom itself has evolved a lot from its beginnings.

Looking at the Communications as a Service landscape, one can see that most of the major vendors have messaging, telephony, and meetings in their portfolio. A small number, e.g. Fuze or 8x8 also offer call center functionality. Microsoft Teams offers collaboration and Cisco’s Webex supports collaboration and call center.

Zoom, without Five9, offers neither of these functionalities, which makes it vulnerable, especially in direct competition with a software that is as ubiquitously available as Microsoft Teams. The vulnerability is the risk of being pushed into a niche instead of staying the top dog that Zoom still is at least in the videoconferencing/video meeting market. Zooms reduced, yet still impressive, growth, is indicating this vulnerability.

On the other hand, the company is awash in cash and can draw off its still high valuation, which it did to acquire Five9.

Zoom is a top dog when it comes to meeting solutions, with its additional solutions it plays pretty strong, but not decisively so, in the market of communications solutions. Five9 is a serious player in the cloud call center software space.

With these areas merging, both players have lots of parts that the respective other does not have. Think video call centers, or video assisted support and remote control. Combining this is a strong value proposition in the short- to midterm.

I do not fully buy in to the story of the proposed “omnichannel engagement platform” as I do think that some crucial aspects, like the ability to identify and profile a customer and her complete context, are missing. I rather see an omnichannel engagement execution platform. Add the profiling part, as Twilio did with acquiring Segment, and we have a really compelling story, especially if Zoom Phone takes off. Having access to the call center, consented customer profiles, and the access to the consumer customers’ devices via Zoom Phone could totally change the game.

Until this happens, I do not see much that hasn’t been done before, although the respective offerings of Zoom and Five9 may well be better than the ones offered by the companies I mentioned earlier.

Still, a good, yet expensive, move that raises the appetite for more.

]]>Fri, 23 Jul 2021 15:15:21 -0400<![CDATA[How to create customer experience with blade technology]]>https://www.aheadcrm.co.nz/blogs/post/how-to-create-customer-experience-with-blade-technology

Starting with the concept of blades we went across a number of different topics related to customer experience with our guest Denis Seynhaeve.

Denis is the CEO of 3CLogic, a company that is dedicated to 'pluggable' contact centers in the cloud, helping organizations to provide good customer experience via voice technology.

So, naturally a number of questions arises. What is blade technology (hint, it doesn't have anything to do with the blade runner but is closer to the blades used in data centers ...)? How does this technology contribute to a customer experience? Why choosing AWS and not another hyperscaler - or run out of own data centers? And, first, and foremost: Why the concentration without exclusivity on ServiceNow? Here, Denis clearly has a strategy that differs from the one pursued by Richard Rosen of Fastcall, who has an exclusive focus on Salesforce.

And, last but not least the fundamental question: How to choose the right ecosystem to play in, if one is not an 800-pound gorilla?

Answers to these questions and more in our CRMKonvo

https://youtu.be/Hm5vRu8Y2LQ
]]>Tue, 06 Apr 2021 08:54:04 -0400<![CDATA[Customer Service in a World of Ambient Computing - The Service Center View]]>https://www.aheadcrm.co.nz/blogs/post/customer-service-world-ambient-computing-service-center-view
A few weeks ago I wrote an article about customer service in a world of ambient computing. This article looked at customer service from a customer’s point of view. In it I described how I see customer service getting humanized again by leveraging the advances in AI technologies like Natural Language Processing, speech-to-text- and text-to-speech generation along with intent determination. Leveraging these technologies customer service will turn into a conversation and it won’t matter anymore whether service is delivered by a bot or by a human. For the customer it will all appear to be the same. Instead of FAQs or web searches, bots will be the first line of support and escalate a problem to humans if they cannot solve it on their own. The obvious question is whether there will be an impact on the customer service center? And it probably does. Call centers, and with it the service agents as well as their managers, already now are under intense pressure to deliver, and to deliver more efficiently. With the increasing use of call deflection technologies like FAQs and communities there is a trend for the incidents facing the agents becoming more challenging. For example Helpshift states that already with its technology it is able to deflect about 90% of all incidents, which are solved via the native in-app FAQ that is delivered by the them. This statement basically says that the support staff is basically relieved of dealing with simple matters but has the chance to take up the more challenging ones. Still, in a world of ambient computing any given app can have hundreds of millions of users. Let’s say that any given day just one per cent of 100 million users have an issue. The well working FAQ deflects 99% of these. That leaves the service center with 100,000 calls. In one day. And they are the harder ones. Still, let’s be optimistic and say that an agent can solve 10 issues an hour, giving him 80 in an 8 hour shift. This would mean an overall call center size of 1,250 agents is needed to cope with this demand. Each of them under a tremendous stress level. With the systems behind bots becoming more and more intelligent the difficulty of raised issues will increase, even if FAQs and web searches are essentially hidden behind a bot interface that essentially makes the human agent the second point of contact again as opposed to the third, which likely means that the customer’s level of annoyance is slightly less elevated than in a third level scenario. At the same time it seems that call center agents are not prepared for handling this stress level. The employee turnover rate remains high and is probably even rising.

What Does This Mean For The Service Center?

Call centers are therefore facing a double challenge
  1. Contain cost. This is achieved by more automation, which in turn puts more strain on the employees
  2. Employ and retain a highly skilled set of service agents, which additionally have matching character traits, which drives cost. Skilled people tend to be more expensive than unskilled ones, and moving a call center into a low-salary country helps only so much – if at all. Training comes at an expense as well. This will be somewhat augmented by reduced hiring cost
The solution to it will be multi-faceted and increase a trend that is already visible. Implement intelligent systems that more than offset the higher salaries demanded – and deserved – by the fewer call center agents, through an increased solution rate and through them being of more help to the service agents. These systems will significantly rely on machine learning out of a variety of sources Employ communities by incentivizing to other users to help other users. These communities will be managed by community managers, with increasing support by AI-driven bots. Highly data driven prioritization and intelligent grouping and routing of incidents to the best matching agent, bot or human. This will involve sophisticated Natural Language Processing capabilities but will help in solving multiple calls regarding the same problem in one process Improved collaboration, bot – bot, bot – human, human – bot, human – human, to further increase the service center’s efficiency. Bot to bot collaboration and bot to human collaboration are for smooth handovers, as for the foreseeable future bots will stay focused on narrowly defined scopes. Human to human collaboration is again a smooth handover to the right expert, but is also about educating the colleague by helping out with own specialized experience. Finally, human to bot collaboration is about the human training the system on the go. Last, but not least, by hiring the right people. An early 2017 study by Harvard Business Review on Kick-Ass Customer Service revealed that call center managers are hiring the wrong people. In scenarios that increasingly deflect calls it needs more highly trained controllers and rocks with a mindset for collaboration, rather than empathizers. While empathy is important what matters most when dealing with a customer in an aggravated mood is a fast and efficient resolution. With this, the role of the manager will change, too, into the direction of being a servant to the team and taking care of roadblocks for the agents and fostering collaboration. This collaboration mandatorily extends into the product department. The best issue is the one that doesn’t even occur. Data from the call center, and from the app itself, gives unique insight into possible problem patterns. And the best problem to have is the one that doesn’t even occur. DevOps gives an idea on how this can get achieved. Ah yes, don’t script too much. Scripts are a good guidance for someone unknowledgeable, which the future call center agent is not. The future of the call center lies in a high degree of automation, powered by highly skilled and motivated agents. That brings the human back to customers and agents alike.
]]>Fri, 11 Aug 2017 09:51:14 -0400<![CDATA[Salesforce Aims At Making Life Easier For Agents]]>https://www.aheadcrm.co.nz/blogs/post/salesforce-aims-making-life-easier-agents
On July 27, 2017 Salesforce announced the availability of an update to their customer service platform Service Cloud. According to Keith Pearce, VP Marketing, Service Cloud, differentiation in customer service is no more a topic within industries, but across industries. Today, customer service in companies competes against the impression gained in another industry, telco vs. banking, vs airline, vs. … you get the picture. Consequently, winning organizations are concentrating on three areas:
  • platform
  • productivity
  • mobile
However, this focus can potentially slow down these organizations because they normally come with trade-offs, like scalability vs. speed of deployment, ease of use vs. complete information, or mobility for customers vs. mobility for agents. Salesforce wants to address these trade-offs with this release by making the solution very easy to set up, easier to customize and enhance, easier to use and finally by offering a new mobile app for agents and supervisors. There is a scripted set up that lets admins deploy a usable application in a short time; Salesforce speaks of less than one day. A component library helps in easily adding relevant functionality via drag and drop in a simple application builder. Of course there are additional components and applications available via the AppExchange market place. Agents shall be made more productive by a clean Kanban-style UI, a tool called Community360 that helps in surfacing community content that a user reviewed before logging an incident, a federated search that is capable of searching across open search compatible providers, and the ability for agents to script tasks. Lastly, there is a new mobile app for agents and supervisors. Here is the complete announcement in case you do not want to follow the link above. Alternatively you can directly continue with my take on this release.   Salesforce Delivers the Next Generation of the World’s #1 Customer Service PlatformWith the new Service Cloud, built on the Salesforce Lightning component framework, companies can deploy a customizable, modern customer service platform in a single dayNew Service Console innovations improve agent productivity, making it easier for companies to provide personalized, differentiated customer service  New Service Cloud Mobile app lets agents manage and resolve cases anytime, anywhere SAN FRANCISCO—July 27, 2017—Salesforce , the global leader in CRM, today introduced the next generation of Service Cloud, the #1 customer service platform. Built on the Salesforce Lightning component-based framework, companies can easily configure and set-up Service Cloud for their organizations in less than a day. With Lightning-Ready partner apps and Lightning App Builder for Service, companies can easily customize and extend Service Cloud. In addition, a new Lightning Service Console adds several new capabilities that boost agent productivity, and a new Service Cloud Mobile app empowers agents to provide exceptional customer service from anywhere. And with Salesforce’s interactive learning platform, Trailhead, anyone can learn for free how to deploy and customize Service Cloud. The new Service Cloud addresses the needs of today’s consumer, who increasingly expect service experiences that are fast, personalized and available through their preferred channels. Yet, many companies today struggle to provide modern, personalized customer service. Established companies often have inflexible, legacy customer service systems, making it difficult and costly to improve existing support channels or add new ones. Smaller companies are often forced to make trade-offs between selecting a lightweight helpdesk for their immediate needs, as opposed to a more robust solution that can scale for future growth. Introducing the Next Generation of Service Cloud Service Cloud provides any company, regardless of size, with a flexible, modern customer service platform that is quick to set-up, easy to learn and can be customized to meet their needs today and in the future. New innovations for Service Cloud include:
  • Service Out-of-the-Box lets companies build a modern customer service center in a single day. Case management is now pre-built into Service Cloud, and a new streamlined set-up experience simplifies the steps needed to deploy essential service flows—with clicks, not code. Service admins can add a customer community and knowledge base, as well as connect to email, Facebook and Twitter feeds—some in as little as five steps. And wIth Trailhead, Salesforce’s online, gamified learning platform, anyone can take one of the 20+ free, guided modules to learn how to deploy, configure and customize Service Cloud.
  • AppExchange and Lightning App Builder for Service provide customer service teams with an easy way to customize and extend Service Cloud. Using the Lightning App Builder, companies can extend functionality by simply dragging-and-dropping one of the new service Lightning Components--such as the knowledge sidebar or related record--into Service Cloud. Companies can further extend Service Cloud functionality with more than 75 Lightning-Ready service partner apps available today on the AppExchange, the world’s largest business app marketplace.  Among the service apps available today are telephony and call center management capabilities from Dialpad, NewVoiceMedia and Talkdesk; IoT asset tracking and mapping from MapAnything Live; and patient education from Healthwise.
  • Lightning Service Console, the unified desktop experience for customer service agents, includes several new capabilities to maximize productivity and speed so agents can provide better customer experiences and resolve cases faster.
    • Case Kanban provides a visual dashboard of cases in queue so agents can more efficiently triage cases and prioritize their time.
    • Community Agent 360 gives the agent useful context, surfacing a customer’s community history and showing if the customer recently viewed or created content, such as a reading a community article or posting a comment.
    • Federated Search helps an agent quickly find records across Salesforce and external data sources such as Confluence, YouTube, Dropbox and Box.
    • Macro Builder lets agents quickly create reusable macros for specific customer service scenarios that agents can easily deploy if the issue arises again.
  • Service Cloud Mobile app for iOS and Android will empower agents to provide personalized customer service from anywhere. With the new native mobile app,  employees will be able to triage, manage and resolve cases while in meetings or on-the-go. Push notifications will help keep agents up to date on the status of their cases, making it easier for them to provide customers with fast, responsive service.
Comments on the News:
  • “Service Cloud is the market leader because of our unparalleled track record of innovation,” said Mike Rosenbaum, EVP, CRM Apps, Salesforce. “The flexibility of Salesforce Lightning and the Service Cloud platform enables us to move quickly and break down technological barriers, so our customers can focus on what matters most for them—delivering truly differentiated service to their customers.”
  • "Every company recognizes the importance of providing good customer service. But for smaller companies, setting up a new contact center is often overwhelming and for bigger companies, they are often constrained by old, legacy systems," said Rebecca Wettemann, VP, Research, Nucleus Research. "With today's announcement, Salesforce is making it much easier for companies all sizes to provide differentiated service."
About Service Cloud Service Cloud, the world’s #1 customer service platform, enables companies to transform the customer and agent experience with an AI-powered, agile platform built for the modern era. Whether engaging customers via messaging, video, communities, web chat, in-app, email, phone or even communicating directly with IoT-connected products, Service Cloud helps leading brands use service as a competitive advantage by delivering personalized, connected customer service experiences across every channel and adapting service operations to business needs quickly. Companies that have deployed Service Cloud have seen an average of 31 percent faster case resolution, an average of 28 percent increase in agent productivity, an average of 26 percent increase in customer retention, an average of 22 percent decrease in support costs, and an average of 35 percent increase in customer satisfaction, according to a third-party research report sponsored by Salesforce. Salesforce has been recognized as a leader for nine consecutive years in the Gartner Magic Quadrant for CRM Customer Engagement Center. Additional Information Connect with Salesforce About Salesforce Salesforce, the Customer Success Platform and world's #1 CRM, empowers companies to connect with their customers in a whole new way. For more information about Salesforce (NYSE: CRM), visit: www.salesforce.com. Any unreleased services or features referenced in this or other press releases or public statements are not currently available and may not be delivered on time or at all. Customers who purchase Salesforce applications should make their purchase decisions based upon features that are currently available. Salesforce has headquarters in San Francisco, with offices in Europe and Asia, and trades on the New York Stock Exchange under the ticker symbol “CRM.” For more information please visit http://www.salesforce.com, or call 1-800-NO-SOFTWARE.

My Take

This release mainly focuses more on agent experience than on customer experience. It delivers a number of useful improvements of the Service Cloud. I particularly like the Service-Out-Of-The-Box capability that helps in easily setting up a working environment. To me it seems very similar to Amazon’s Cloud Connect that can get setup with a few clicks only, but goes beyond it with its customizing and enhancement abilities. In combination with attractive pricing (of which I don’t know whether it is there or not) this has the potential of making Salesforce Service Cloud more attractive for smaller companies again. Still it needs some more steps, e.g. in facilitating an Einstein-supported routing of inbound service requests via its contents instead of having one email address per queue (topic). The second very useful feature is Community360 that gives context to the agent the moment a recognized user calls in. With this agents do know what the user looked at and can get into a more focused research right away. Unluckily at this time it requires the customer to be logged in to properly match the calling customer to the corresponding search history. As useful as federated search is – this is ability probably long overdue, although there are admittedly complexities in the management of authorizations when searching across corporate document repositories. The mobile app to me is a kind of round off. One simply needs to have a mobile app nowadays, but the added benefit for most organizations is limited due to its limited screen real estate. In my mind it should not get overvalued outside notifying managers or escalation contacts to get back to their screens or help a struggling agent. Smaller organizations or ambitious agents might use it to go the extra mile outside office, but it cannot be the main tool. Overall I think that Salesforce brought some well thought through enhancements that can add value to businesses. On the concern side, some of them seem half baked but are paving the way for future improvements.
]]>Tue, 01 Aug 2017 09:28:07 -0400<![CDATA[CustServ Solutions - Why Choose one Over the Other?]]>https://www.aheadcrm.co.nz/blogs/post/custserv-solutions-choose-one
For a while now I am contemplating about why companies choose one custserv solution over another. After all the market is pretty crowded. Vendors have a hard time to differentiate themselves. Just looking at G2Crowd one finds 88 Help Desk Solutions. Larger organizations are likely to be influenced by Gartner’s Magic Quadrant on Customer Engagement Centers or the Forrester Wave on Customer Service Solutions. Smaller organizations are probably looking more at the new breed of peer-to-peer review sites, like the aforementioned G2Crowd or GetApp, TrustRadius, Capterra and others. Many companies conduct research and establish an RFP process to determine the best fit; some see a bottom-up approach from team level to corporation. A kind of ‘shadow IT’ emerges to solve a team’s particular problem. This solution over time could get corporate blessing and may even become the main solution. A clear and reliable roadmap is mandatory for all vendors, so no difference here. Same for share of mind – this has become table stakes. But what is it that makes one vendor win over another? Are there patterns? To get more insight I asked some smart people who stay unnamed here – but you know who you are!

So What Are Contributing Factors?

The good news is that there seem to be only a few factors. Based on the discussions I can roughly group them into six categories. Here they are, in no particular order:
  • A particular feature is needed or desired
  • Suite- vs. Best-of-Breed thinking
  • Size of the customer organization
  • Relationship building
  • Referrals
  • Departmental adoption
Of course they are not mutually exclusive. Let me briefly dive into each of them.

Need of a Particular Feature

This is something that helps nimble specialty vendors that either already offer a very particular feature, e.g. support for mobile applications, a Google-like search through an FAQ, an FAQ that is available offline, or the philosophy of treating service requests as a conversation instead of coming from a ticket point of view. The former emphasizes on the customer, the latter on the service provider. With the probable exception of the philosophy approach this contributing factor does not provide a vendor with a lasting advantage; successful features can – and will – be copied in a short time.

Suite vs. Best-of-Breed

Helpdesk software should not be a silo of its own but be integrated into the other business systems. As one of my contacts said “there is some convergence”. However, integration is a very complex topic. Some vendors are therefore offering tightly integrated software, usually on cost of some breadth or depth of functionality and are successfully selling this as an advantage. Customers that go the suite way are usually more interested in a holistic approach than a complete fit to all needs. On the other hand Best-of-Breed vendors are focusing on providing the best solution while maintaining a small footprint and while increasingly offering integration via platforms. This is usually achieved by having prebuilt integrations and partnerships with platform vendors and therefore by joining (or creating) an ecosystem of vendors. Still, customers opting for Best-of-Breed often look more into a strong functional fit to their requirements.

Size of the Customer Organization

As one of the persons I talked to said, “You cannot be wrong if you decide for IBM” was a slogan back in the 80s that pretty well describes the behavior of large organizations. Risk averse, following the mainstream – almost driven by fear. Although this is no more that prevalent, one can still observe that larger, more centralized organizations favor the incumbents over new best-of-breed solutions. This results in a tendency towards suite solutions. Organizations that give their units more independency tend to be more nimble, like smaller organizations, and are more accessible for best-of-breed and departmental solutions.

Relationship Building

Relationships are a powerful tool. Vendors that are able to demonstrate that they are not only after a sale but also want to become reliable partners to their customers can get a distinct advantage, especially when showing an outside-in focus that focuses on continuous benefits to the customer. Strong relationships serve as a barrier for competition, and create the opportunity for internal as well as external referrals.

Referrals

Referrals are the strongest marketing that a vendor can use. Regardless of best-of-breed or suite, referrals get earned by building a relationship and delivering up to promise. This is doubly true in times where trust implodes and is in crisis mode with people mainly trusting “someone like me”. Be it the groqing out of a department of a solution, or the win of an additional customer, satisfied customers who turn advocates are key.

Departmental Adoption

Land and expand! This is a proven strategy for small and aggressive vendors, enabled by cloud delivery models. Especially in organizations with decentralized decision-making this is a good approach to get functional pain points alleviated quickly, albeit often at the expense of a corporate strategy.

What Does It Mean?

Different criteria have different impacts and need to be looked at from different angles. However, one thing is clear: Relationships and referrals are key components in the mix. Suite- as well as Best-of-Breed vendors are well advised to build strong partnership relationships with their customers. For both types of vendors this brings new customers and for Best-of-Breed vendors it additionally opens the door from the department into the main enterprise.

Suite Vendors

For big suite vendors it is hard to do a departmental sale. Examples for this category of vendors are SAP, Oracle, and Microsoft, or formerly Netsuite, probably also Zendesk. Their solutions are regularly (with some exceptions) geared to the large enterprise where also the deals are bigger. Relationship building encompasses building relations to a number of stakeholders and correspondingly takes more time. These vendors need to be able to make a strong point on easy process integration plus getting the right feature-set into the solution. Their being confined to the enterprise market is their biggest problem and they need to be able to act like Best-of-Breed vendors. The emergence of <take your pick> clouds shows that they are working on this.

Best-of-Breed Vendors

In contrast to suite vendors, Best-of-Breed vendors can concentrate on particular, important and distinguishing features. With that they also focus on a smaller set of industries and customer sizes. Due to their focus they are often able to maintain an advantage. Good examples here are Helpshift, or Freshworks and, surprisingly, Salesforce. An odd assortment? No. Helpshift is a pureplay, albeit with a focus on bigger customers. Freshworks and Salesforce offer a variety of solutions, with Freshworks covering the SMB market and Salesforce the upper M and enterprise markets. I do not name them suite vendors, as both sell disjoint products that can be integrated via a common platform. Salesforce here became big by using a ‘land and expand’ strategy, which it still uses. For vendors in this group it is important to show the right feature fit for their audience plus the ability to integrate into other systems, to not get marginalized. Helpshift has the clearest focus with a strong, matching feature set, and a tight integration into Salesforce. Freshworks and Salesforce are offering a number of specialized applications that can integrate through their own platforms – and offer marketplaces to attract specializations that they do not offer themselves. And there is Nimble, which is in a different area, but has a very interesting strategy. The company positions itself as the ‘entry drug’ into a larger ecosystem, with a tight focus, augmented by a clear growth path for their customers. And with relationship sales par excellence. In conclusion: There is a simple framework but the secret is in the mix. And the mix differs for each company. Use the right arguments for the right customer.
]]>Fri, 28 Jul 2017 08:13:40 -0400<![CDATA[Customer Service in a World of Ambient Computing]]>https://www.aheadcrm.co.nz/blogs/post/customer-service-world-ambient-computing
Soon there will be an additional in-app customer service channel. So far we have a bunch of service channels, most of them requiring the user to leave the app to
  • Pick up the phone for a call
  • Browse for self support
  • Open up an additional chat window
  • Take on the social media channels
  • Move on to messenger applications
  • How about getting into your car to get to a store?
  • ...
And then a customer may be moving back and forth between these channels with all the potential of losing track of the incident status and the friction that cross channel customer service still causes. There is no doubt that providing in-app support is the best possibility to offer fast issue resolution. It can provide telemetry information from within the app, identify the user and therefore provides a lot of relevant context that makes it easier for a service agent to help the customer without unnecessary delays. The customers’ shift to emphasize on the “Now” is also seen by Google research.

Not Every Device is a Smartphone

But what if the customer cannot pick up the phone to engage in a typed conversation? The customer might be engaged in a VR game, or driving a car, or in any number of situations without having a free hand. Maybe the customer simply doesn’t want to pick up a phone? What if the app doesn’t offer a user interface at all beyond a little light that indicates ‘I am available’? This would e.g. be the situation in an ambient environment that senses the presence of a person and acts accordingly. An environment like this would mainly be voice and gesture controlled via devices like Amazon’s Alexa, Google Home, Apple’s HomePod, or Microsoft’s upcoming Home Hub. Systems like these will offer a keyboard as a secondary means to access service and support at best. But there is no need to look that far out. Imagine a gaming situation. Neither an Xbox, nor a Playstation, nor any other major controller offers a keyboard. In case of these or a VR or AR game the user would hold the controller and doesn’t have the leeway to get to a keyboard. So why would they offer a keyboard to enable conversational (or other) in-app support? There is no reason. Instead users will interact with the service system and –agent via gesture-, view- and speech based interfaces.

The next In-App Support Channel is Voice

Voice recognition technologies are maturing rapidly and start to achieve human level accuracy in understanding at least English language. Human level of understanding lies at a word error rate (WER) of about 5 per cent, which means that a human on average gets five out of hundred words wrong due to misrecognition, missing a word, or falsely inserting one. Machines arrive at human level of language understanding; source 2017 Internet Trends Report Machines arrive at human level of language understanding; source 2017 Internet Trends Report While Amazon doesn’t give any numbers on Alexa’s capabilities, Microsoft announced it reached a word error rate (WER) of 5.9 per cent in October 2016; IBM beat them to the punch with a WER of 5.5 percent in March 2017. And Google announced in May 2017 that it reached a WER of 4.9 per cent. Using speech recognition techniques on a level like this, in combination with natural language processing (NLP) and perhaps natural language generation (NLG), in-app service conversations can get both, very personal, and very immersive. And very effective. Speaking is the form of communication that comes easiest to humans. Speaking and conversations are tightly linked. Last but not least it is also a very efficient way of providing customer service as the human ability to exchange information is highest when speaking.

Bringing Human Back To Customer Service

Right now customer service 2.0, the automation of customer service, seems to move from call deflection via self-service and then bots to customer service 3.0. Helped by increasing maturity of NLP- and intent detection technology this iteration will move the bots from the second row into the front row. They will become the primary customer support interface. Instead of using a search box on an FAQ, customers will ask a bot for help via a chat interface. The bot itself then will be able to answer the question using e.g. an FAQ or database, or escalate the question to a human operator. The distinction between self-service and aided customer service will first blur, then vanish. The machine takes care of the simpler problems, the human of the more difficult ones. With further refinement of Natural Language Processing, text to speech-, speech to text technologies and intent detection, typing will give way to speech again, then introducing customer service 4.0. Customer service will fully turn into a conversation and it will not matter anymore whether it is synchronous or asynchronous. It also will not matter anymore whether customer service is delivered by a bot or a human, but will appear human. And that might have an impact on the call center and its operation itself that we will look at in a separate post. The bottom line is: Customer service will be humanized again.  
]]>Tue, 11 Jul 2017 07:48:23 -0400<![CDATA[Agent.AI - Customer Service with the AI Bot]]>https://www.aheadcrm.co.nz/blogs/post/agent-ai-customer-service-ai-bot
Earlier in June I had the opportunity to talk to Barry Coleman, CTO of Agent.ai, an about 2-year-old company at the time of writing this. The company spun off of manage.com, a very different business that enable the delivery of in-app advertisements. In order to support this mission more and more, first internal, then external support capabilities were needed. At first they built chat functionality for internal and for support purposes. Then there was the question of how to efficiently provide 24/7 support. This resulted in giving birth to a bot structure that can help customer service agents in an assisting mode, called co-pilot mode, and an autonomous mode, called autopilot. And it gave birth to Agent.ai. Agent.ai’s mission is to enable “exceptional customer service for all”. While this mission is not particularly unique, their approach is. First, Agent.ai has built its customer service software around a machine-learning platform. Second, the company provides their solution without asking their clients for a huge upfront investment or the need to have of AI-proficient developers in house. Third, they wanted to avoid the pitfall of inflated expectations. With AI and machine learning being very hyped topics at the moment, this is a very valid concern. Going backwards through the objectives, Agent.ai opted for offering very specialized bots first. As there is no general AI yet, this is pretty straightforward. Specific, tightly framed topics are far easier to support with AI and exposed by bots than broader bodies of knowledge. For example, specializations include the handling of order inquiries or of support call closure surveys. The second objective was achieved by doing all the heavy lifting, including the customer specific training of the AI in their own system, by providing specialized bots, and by offering APIs for their customers to implement own specialized bots. One interesting aspect is that Agent.ai’s software fabric allows the individual bots to collaborate with each other and communicate internally with agents and externally with customers. This collaboration is necessary due to the strong specialization of the bots and is mainly controlled by a ‘central’ AI-based bot that resides in the Agent.ai infrastructure, called ‘AVA’, which is an abbreviation for Automated Virtual Agent. AVA is the brains of the system. The job of the AI bot is to understand speech and to identify a user’s intent using NLP, neural networks, and deep learning. This intent could be a request for information or a call to support an incident. With this done the AI bot dispatches the incoming request to the corresponding specialized ‘intent’ bot that can take up the transaction and hand it over to another bot, or escalate to a human agent in case they get stuck. The system is trained from a variety of sources, such as FAQ, existing documentation, and e-mail trails. Chat transcripts prove to be especially valuable as they allow for identification of both, problem and a solution. These transcripts also offer an excellent means for continuously training the bots while being in co-pilot mode, the mode in which they suggest answers, along with a confidence level in the answer, to human service agents. The usage of chat protocols along with the service agents choosing to use bot recommendations or not, allows for constant recalibration of suggestions’ confidence levels. Which leads to the topic of trust; user trust as well as agent trust – and to the question when a specific bot can be put into the wild and work autonomously. The answer to this is surprisingly simple although there is no explicit measurement: If suggestions consistently exceed a defined high confidence level then the bot is good to go unsupervised and escalates issues it cannot answer itself to a human service agent. Another possibility of identifying trust levels is the change of customer sentiment in the course of a transaction. Working in co-pilot mode, with the ability to have bots work unsupervised, human agents free up the time to work on novel problems. Typically, these can be the issues that bots haven’t been trained for, and maybe cannot be trained for. Barry emphasizes that “human-machine cooperation is really important”.

My Take

Agent.ai has an interesting story to tell. The idea of offering an affordable infrastructure to provide 24/7 mobile in-app customer service using bots that are driven by machine learning and AI is probably not new but consequently implemented. Bots can considerably speed up the support transaction by continuously listening to specific queues. With well-trained bots this can lead to positive support experiences by showing that a customer’s time is valuable. This also applies to the co-pilot mode, when the bots can already prepare suggestions along with confidence levels that help the service agent prepare herself for an issue. In addition to providing a toolkit for mobile in-app support, Agent.ai is supporting nearly all major messaging platforms, which allows for richer customer profiles as well as for a wider reach for both, Agant.ai’s customers, and Agent.ai itself. Agent.ai’s customers can offer their customers availability on the channels they prefer without being in the need to look for additional vendors to cover different messaging channels. Agent.ai’s bot-driven mobile first approach puts the company into an interesting position. Mobile in-app specialists normally do not support messaging services with the correct argument that the service engagement can be made far more personalized. This is due to more information being available to the service agent via the SDK. It simply can provide more information than the messaging service will ever do. On the other hand there will be many users who simply do not want to install vendor apps. Integrations with Zendesk and Salesforce give exposure to the world of the ‘big guys’. Zendesk does believe that bots are not yet far enough to be really useful in customer facing service interactions. Meanwhile Salesforce does not have any bot capabilities either, as far as I know. Both companies offer integration into major messaging apps, with Zendesk also offering an app SDK, though. Still, this leaves an opportunity for innovative vendors. I believe that the strategy of covering the breadth of mobile along with the ability to cover small to big customers is pretty strong. It puts Agent.ai dead into a spot that no major vendor covers, while at the moment having a technological advantage. However, there are also some concerns. I suspect that the approach of taking away the ‘heavy lifting’ from customers may lead to consulting services, which do not scale well. In addition Agent.ai is a young company, which always raises the fear of viability. Agent.ai says it has more than 1,000 customers from small to large in different industries. These customers are using SDK and web client most, followed by the Facebook Messenger. While this sounds like a big number there is no information on actual users. Still, this is a company to watch.
]]>Thu, 29 Jun 2017 09:23:21 -0400<![CDATA[Customer Service - How to Turn a Poor Experience into a Positive One]]>https://www.aheadcrm.co.nz/blogs/post/customer-service-turn-poor-experience-positive-one
With mobile phones taking over our lives and conversational interfaces becoming ubiquitous there is certainly a new level of demand arriving at customer service centers. Customers do not accept a mediocre service experience anymore. With their smartphones they have the means to get to customer service with nearly no delay and they are certainly willing to use it. And they do it. In this situation customers are often already feeling some frustration or disappointment because they couldn’t achieve what they wanted to achieve in the first instance. They already had their taste of a suboptimal customer experience. Frustration, disappointment – customers’ negative emotions towards a brand have a corresponding negative impact on the business. Customers just might go buy somewhere else. After all, in times of smartphones this has become simpler than ever. The support center now has best chances to add the feeling of being disrespected and outright anger into the mix. Or it can create a feeling of relief, of being respected, valued, even some satisfaction; this in spite of having come into the need of asking for support. Here the service agents have the opportunity to create a positive customer experience out of a poor one – one that will overlay the negative one.

Use Customer Service To Create Positive Emotions

Benefits of investing into experience Source: Sitecore/Avanade Which one is better for the company – and the company’s bottom line? The answer to this question is pretty obvious. Inmoment Research recently released a study that clearly established links between positive experiences and positive outcomes for a company. And this was not the first study finding that investing into positive customer experiences results in positive outcomes for the company. A 2016 study by Sitecore and Avanade showed a number of tangible business benefits that can be related to this investment. The open secret is that there is an easy way to turn a customer who is on the edge into a satisfied and happy one. This way works around recognizing what the customer values:
  • Their time
  • Their channel
  • Getting their issue resolved
This way clearly involves the smartphone. After all this is the switchboard of their lives and in all likelihood also the device where the issue occurred.

Go Social? No Way!

You may say: “Go social! Twitter, Facebook! People go there all the time! And they are getting fast and efficient help there!” Do they? Most customers aren’t getting fast and efficient help on social networks. Only few do. Mainly those with loud voices, because of having large follower numbers. And why are people resorting to social media? They use them as a last resort after the traditional ways didn’t work. In other words, because they are disappointed, frustrated and likely even angry. So they act as derailers of the brand, instead of being brought on the way of becoming promoters or even ambassadors.

Resolve Issues Fast, The Customers’ Way

This is where conversational interfaces, messaging and mobile in-app support come into the picture. This combination allows a customer to directly cut through to efficient service instead of repeatedly iterating through information they have already given before. Via the app the customer and many of the interactions (s)he did before the incident are already known. An agent can get to work directly, maybe even supported by a bot as a copilot, or even an autonomous one. The emotional advantage starts right in the beginning. In most of the cases the customer is already known and can be addressed by name instead of being in the need of introducing him-/herself. And due to the information that is already available the issue has been routed to the right service agents who in turn can get right at work when the ticket arrives on their desk. And this may very well be before they even reply, thus giving themselves the chance to be equipped with relevant knowledge and perhaps already a solution suggestion. As a result the customer feels treated respectfully and with appreciation of his/her concerns and time. Now, it is an illusion that every call center has enough staff to be able to immediately react to every incident and inquiry customers may have – ideal but an illusion. There is nothing worse than the electronic equivalent of holding music and the repeated statement that “your call is important to us”! Its mere existence actually proves the contrary.

Use AI to Improve the Experience

This is where AI and machine learning, exposed by chatbots take center stage. In a supportive role the AI can already supply the agent with possible solutions to the incident at hand before the agent takes up the issue. These solutions can get derived from the FAQ, internal documentation, a community, or from previous incidents that dealt with a similar topic. The ranked listing of suggestions can then be presented to the agent by a chatbot as part of the conversational interface that is used in between customer, service agents, and the technology. This already has the potential of significantly speeding up the resolution process, thus addressing what the customer values. It is a better engagement model that likely creates a positive experience – maybe a little wow moment. When enough trust has been established to the AI, the chatbot can get into an autonomous role and engage with the customer before an agent takes over. The human agent then becomes the escalation point for issues that the system cannot resolve without human interaction. To get into this escalation the bot could offer and schedule a callback by a person or simply do a handover to the next service level after informing the customer about the necessity for this. In this model even an explicit FAQ can be made obsolete as the chatbot can serve as a front end to it.

The results?

Conversational interfaces, alone or supported by chatbots have a profoundly positive impact on the business. The main benefits are:
  • Customer service is addressed the customer way
  • Faster incident resolution
  • More satisfied customers who have a better customer experience
Satisfied customers have more positive emotions about a company. A positive base is more likely to perceive an engagement as positive, which means it turns into a positive customer experience. And positive customer experiences create positive business outcomes. It is that simple.
]]>Sat, 17 Jun 2017 08:19:50 -0400