qpod

Two AI Use Cases for Customer Support and Services

In our last post, we highlighted the fact that many companies assume that the more “human” parts of business —sales and customer service—have little to gain from Artificial Intelligence. Of course, this assumption is incorrect, and liable to mislead companies who could otherwise stand to benefit.

Consider:

According to Forrester, 72% of businesses say that improving the customer experience is their top priority.
Most contact with customer service now takes place via the web using a chatbot, via email, or via social media. The set of skills and tools needed here are different than, say, handling a case via phone.
Customers have ever-growing expectations with regards to response time. A decade ago, customers were willing to wait 24 hours for an answer to a question or a solution to their problems. Now they want an answer right away…if not instantly.
As business grow and expand their global reach, more and more customer support cases begin to look similar. Solving each case independently is burdensome, if not impossible.
The average customer triage and resolution cycle takes five or more steps having to do solely with information search among the organizations various data sources.

In other words, the need for a human being with “people skills” is diminishing just as the strengths of artificial intelligence agents—such as the ability to query multiple data sources quickly and efficiently—are coming in high demand. Indeed, one prediction holds that, by the year 2020, more than 85% of all customer interactions will be handled without the need for a human agent.

But what does customer support via artificial intelligence agent look like? Again, we can illustrate this best with two use cases around our own knowledge automation solution, Nimeyo.

Use Case 1: Resolving Customer Issues When Knowledge is Siloed

The Context:

Today, customer service reps are expected to resolve customer issues faster and faster, even as they take on huge case volume to justify their job roles. In order to do a good job of meeting customer expectations and succeed in their roles, a single pane of information and knowledge access is essential.

The Challenge:

Again, the typical customer resolution in an organization of any appreciable sizes takes researching five or more data-sources. These include:

Querying customer-facing case management systems (such as Salesforce Service Cloud or Zendesk) to identify duplicates and bring up relevant contextual information
Comparing across internal incident management systems (such as Jira) to find similar cases already being addressed, or that have recently been addressed successfully.
Searching KnowledgeBase articles and wikis for quick resolution of common problems, or concise answers to frequently asked questions
Combing through off-band but relevant conversations in emails or Slack channels

Already, this process is pretty daunting. When you consider that two or more of these steps could be taken for cases that are very similar, and for which solutions already exist, it becomes painfully obvious how much time is wasted and productivity sacrificed. Currently, organizations are struggling to find ways to integrate these various sources into a single pane.

How AI Helps:

This scenario is easily fixed with a solution like Nimeyo knowledge automation. Using Nimeyo, customer service reps can address cases more readily, thanks to instant access to knowledge of similar cases across content silos of customer issues and internal product ticket systems.

Nimeyo can also integrate with management systems like Salesforce, as well as incident management systems like Jira and chat channels like Slack. It can then access these systems instantly and use the information in them to help zero-in on the resolution for a given case, relieving the customer service rep from having to do these searches manually.

More importantly, Nimeyo helps customer service reps deflect more cases by giving them increased visibility of similar cases across customer issues and internal product ticket systems.

All of this results in more rapid response which, ideally, leads to improving their first contact and/or first time resolution times.

Use Case 2: Self-help Bots For Customers and Service Teams

The Context:

As we all know, a lot hinges on having a positive customer service experience: It can mean the difference between a loyal customer, and a disgruntled one. Speed and accuracy matter crucially, and customer demand instant responses. If they don’t find an answer immediately, they are disappointed and are quick to share their bad experience on social media or other public channels.

But increasing complexity of products and services, along with the high turnover rate of most call centers, means that it is almost impossible for service reps to keep up with the content needed to resolve issues in a timely fashion.

These dynamics are fundamentally changing how both customers and service reps seek out information. For example, the majority of Millennials actively avoid situations for which human interaction is necessary to solve an issue, much preferring self-service options instead. One study of the generational divide in customer service found that a whopping 72% of Millennials believe a phone call is not the best way to resolve their customer service issues.

So how are consumer resolving their issues, if not calling customer support? Right now, they are using a mix of chat bots on websites, social media sites for the relevant brands, chat channels, and Google searches. In other words, they are already going with digital self-help solutions.

The Challenge:

Companies face two choices: Either improve the self-help bots they make available, or better empower their service teams to compete with these bots.

Most of the current self-help systems are web centric, so customers are relegated to searching for a solution themselves—and are often confronted with more pages than they are willing to review. Even if they do find the answer they seek, it may not be the most accurate or latest answer.

That said, many Customers are still “put at ease” knowing that there is a customer service rep in the interaction; but this “human touch” engagement is costly, often only available during business hours, and is (for the most part) unscalable.

How AI Helps:

With a Nimeyo AI solution, customer service organizations can create a foundation of knowledge and insights from approved content sources like FAQ databases, product documentation or issue tracking systems. Subsequently, bots or auto responses act as the first line of defense to respond to common question with known answers or fixes.

When a customer sends an email to a support email address, the email autoresponder can look at the knowledge available to instantly respond with links to most relevant answer. If the customer is happy with the answer, then the customer service team can mark the issue as resolved. If the customer indicates that more assistance is needed, a rep can reach out for additional information.

What about availability and scale? Typically, a customer service chat is available only during business hours (unless you have a globally distributed service teams.) However, if a customer initiates a chat with a rep during off hours, an auto responder bot can respond to customer query with knowledge from approved sources. Queries such as the status of a case, answers to FAQs, or product specific questions can be responded to in seconds without any human intervention. Again, the chatbot can be the first line of defense before a rep needs to be engaged.

Again, these are just two simple ways that AI agents are changing the face of customer service. Counter to many of the assumptions surrounding AI, human beings will always have a role to play in customer support, since there will always be difficult cases requires a person’s ability to understand the nuances of the case and find creative solutions. Increased productivity comes when human beings can be freed from routine and easily-solved cases, and allowed to focus on more complex cases and tasks. Artificial Intelligence can potentially leave service reps free to tap into the critical thinking and problem-solving skills, not to mention emotional intelligence, when they are needed most.

If it still sounds like a pipe-dream to empower human interactions through AI technology, we recommend you try Nimeyo yourself to see how this can be done in your organization. Sign up for a free demo, and we would be delighted to give you a tour and show how the Nimeyo AI can be best used by your customer service teams.

Lessons and Challenges from Slack

We at Nimeyo have always been fascinated with how employees communicate, and an intriguing company on the forefront of this is Slack. Slack has succeeded where many others have failed. Heck, Microsoft almost bought it for $8 billion. Given that, what has it done right that we can all learn from and what challenges does adopting Slack create?

How did it get traction?

On the surface, Slack does not look all that appealing. It is, after all, just IM plus channels. But that’s the key to its success. It is not reinventing the wheel nor overwhelming the user. Slack presents something we all know and makes it really easy to use. Just a browser and you are ready to go.

Simplicity is the key, and Slack nailed it. Slack just fits into an employee’s natural workflow.

Making communication conversational

One way Slack fits right into the employee’s workflow is by facilitating conversation. Sure, there are documents, e-mails, wikis – but information often flows through conversations.

And what is a conversation? A series of quick back and forths – something humans are naturally good at. And Slack allows this in an electronic forum.

When it comes to this type of communication, there is always a tug back and forth between structured, formalized knowledge, and informal conversational knowledge. And Slack has succeeded by knowing that employees generally prefer the latter. In other words, people would rather have ease and simplicity– they don’t want to be bothered with formatting, manipulating, or overall shaping the data to something that is useful later.

Doesn’t make the user change behavior

Slack also allows integration with many third party tools and services: e-mail, Box, Google Drive, Dropbox, etc. Employees can still use their favorite means of electronic communication and have that be automatically integrated into Slack. If an employee still prefers e-mail, she can use e-mail. If she wants to put information into a document on Dropbox – no need to duplicate that information into Slack. In other words, Slack integrates, but doesn’t force change. After all, everyone is a creature of habit in one way or another.

But is Slack taking away from organization?

But the picture is not all rosy. Conversations do have weaknesses – they are tough to organize.

With Slack, there’s less need for documentation, formalized transfers of information, seminars, etc. While this saves time, it also means that the expertise will often remain siloed and only be passed on, piece by piece, when needed due to the chatty nature of communication. But in the age of rapid turnover, what happens if an expert leaves? Does all their knowledge leave with them?

And is adding yet another channel of communication worth it?

It’s important to remember that Slack is another tool, and tool fatigue sets in. With real estate space on the screen becoming even more precious and people being pulled in many different directions, very few employees clamor for another tool to deal with.

What can be done about these challenges?

While Slack is a great tool, we at Nimeyo understand the challenges that it presents

Keeps information siloed by detracting from more formalized training methods
Information is haphazardly placed, with little organization, and plain tough to find
Information is in yet another place, making discovery much more of a chore
Yet another tool amongst a myriad of tools that the average employee has to deal with

There are many ways to go mitigate this. Slack provides APIs to integrate channels into whatever management tool you wish. They also have Apps which provide integration with 3rd party tools like Box. Unfortunately, this requires a lot of IT resources from employees who would rather be working on core services.

qPod by Nimeyo provides a ready-built solution by processing Slack information into a searchable, interactive, question and answer system. Information flow can be congregated from various sources like Slack, e-mail, Box, SharePoint, Salesforce, JIRA, Confluence, and much more. And the knowledge gained can be easily accessed to help find the information you’re looking for in bite sized pieces. Information from Slack is more structured, available in the user’s workflow, and can easily be discovered. In other words, qPod takes Slack to a higher level.

qPod and Slack together!

qPod and Slack work well together with our newly introduced “qPod by Nimeyo” Slack App.

Slack integration within qPod allows users to simply login via Slack – no need to setup a separate login username and password.

And once integrated, channel messages can be imported and accessible throughout qPod.

And with our “qPod by Nimeyo” Slack App, accessing qPod and posting information is a breeze with easy to use Slack Commands.

If you’d like to take a test drive, please head over to our Slack App page and sign up.

qPod now available on Amazon AWS marketplace!

We are delighted to announce that qPod from Nimeyo – a “self-help” knowledge system for pre- and post-sales organizations – is now available through Amazon AWS marketplace.

Why AWS?
Amazon Web Services or AWS offers reliable, scalable, and inexpensive cloud computing services.

With our qPod Saas solution exclusively hosted on AWS you can be assured of robust security and data protection guarantees provided by AWS. In addition, for those
customers who use AWS private cloud for added security and control, qPod can be deployed with a single click in their existing VPC!

We continue to strive to make qPod deployment fast, easy, and intuitive so that customers see the value of qPod within minutes of deployment.

Click to learn more

A critical piece to tribal knowledge management in enterprises

Email is the de facto form of communication in the business world. According to the market analysis group Radicati, in year 2013, 929 million corporate mailboxes generated roughly 100 billion emails every day. Moreover, despite all the talk about an imminent demise of email, corporate usage of this medium is expected to grow over coming years. Unfortunately, this most pervasive corporate application is more or less untapped by current enterprise knowledge management tools.

At an individual level, an average employee receives about 150 emails per day, among which about 50 include attachments. Further exacerbating the issue is corporate email retention policies which often conflicts with the needs to preserve corporate knowledge.

So the critical question is – how are your employees able to save and retrieve important information about products, customers, and peers? Are they able to access useful data from years before with ease? If not, then efficiency is being affected.

Nimeyo Inc. recently helped a publicly traded company with a global team of sales engineers deal with a similar issue. The company relied on email communication, particularly inter- and intra-departmental mailing lists like ask-se, ask-experts to triage and resolve customer issues. Unfortunately, the rich set of knowledge hidden in these raw email threads was unusable due to lack of technical solutions to analyse and search. This resulted in iterative and repetitive work that wasted time and effort, reducing efficiency of the team. Nimeyo’s qPod, using its email analysis engines, converted 3+ years of email content into a functional knowledge that provided superior search, usability, and mobility to the world-wide team of field engineers. Moreover, qPod provided bookmarking and personalized search for efficient knowledge retrieval. Finally, qPod continuously refreshed knowledge as new email content got generated, allowing users to stay in the medium they were comfortable with.

If your company is struggling with repetitive discussions on previously explored and resolved topics, if your email systems are in a mess, contact us and see how Nimeyo can help improve your team’s efficiency.

Our product – qPod – solves this exact problem. It is a knowledge base that seeds itself from information that is already around, and more importantly, it continuously refreshes itself as new information flows through various communication channels like email, social feeds, and chat rooms.

If your sales force can use a software that actually helps them do their job better, sign up for the free trial of qPod.

How to Boost the efficiency of the world-wide sales force

One of the most common scenarios we hear while talking to Sales and Sales Engineering teams is that

They are growing fast and it is challenging to scale the sales force to meet the needs of new customers, and
They are hiring new employees but it is a challenge to ramp those employees on product and customer specific technical details.

What further exacerbates the problem is that Sales and SE teams are scattered world wide. Non-HQ employees are at a further disadvantages given their inability to knock on the “expert next door”.

Obviously sales organizations are constantly looking for solutions that can help them tackle these “growing pains” by improving the collaborations and knowledge management processes. Unfortunately, the tools they employ (e.g., CRM software, Wiki pages, document repositories) just don’t work in improving the productivity of the sales reps and SEs (more detailed treatment of this topic to follow).