Here’s Your Coffee. Have a Seat.  

I’m squeaking in a post a week! The New Year has brought new opportunities that have kept me busy, so I’m posting later than I’d like. I have a slew of topics I want to cover for self-service and customer experience (about 30 to date) so I’ll do my best to keep up.


The Use Cases

In Let's Talk About Virtual Agents And Assistants (Part 1), we covered the broad definition of a virtual agent as well as how they work (no subpoenas yet). This week we’re going to look into a bit more of the nitty-gritty and focus on some channel use cases. 

There are three primary use cases for customer facing support: Technical Support, Post Sales Support, and Sales. In all of these cases, escalation or forwarding links can be added as part of the solution or the journey, depending on the question. So not only will a vAgent help with self-service, they are great tools to filter cold prospects for sales, retain important post-sales touches, or escalate tough issues to an agent. Additionally, some virtual agent/assistant vendors can connect to Salesforce where a transcript of the interactions can be passed to email or chat agents.

Technical Support

While I have used vAgents for some really complicated technical scenarios successfully, they work best when used for a limited amount of knowledge solutions - usually around 100 - 150. Believe it or not, this works well for companies that have products that have lots of feature/functionality overlap or only a couple flagship products.

Generally, a vAgent can respond to your most common technical queries as well as some customer service related results. As mentioned in the original post, the data harvest of customer queries for a prominently placed vAgent is a goldmine of new technical questions and trends.

The downside for large enterprises with multiple product lines (e.g., Microsoft), will need to create multiple vAgents - which can be really effective for the top issues. But for complex errors and deep solutions being displayed in a tiny chat window, it will get tedious for users. (Note: in some cases you can get around this by linking to KB articles, but this removes the user from the vAgent session where related metrics are gathered).

An additional tip is to use broad categories, such as error codes, product functionality (how-to's), product maintenance (updates, upgrades), or product information (compatibility, requirements, etc.). It may seem logical to duplicate your knowledge base hierarchy here, but it could lead to increased customer effort. vAgent’s are supposed to be a more causal, less intimidating experience than using a huge list of FAQs or browsing your KB. So try to simplify your categories into larger groups as in the break down above. 

Post Sales Support

Virtual agents excel at answering queries on upgrading, refunds, policies, email subscription preferences, privacy, and other cold prospect/noise questions that take up expensive agent time.  A vAgent will easily prove its ROI in both low and high volume contact centers where live support is limited in staff and time.

Many times, Sales topics are small enough to be combined with technical virtual agents or sales virtual assistants. These types of post-sales support questions tend to hit both technical and sales channels and should be included in both to reduce escalations or channel them to relevant live agents. 


Sales is where a virtual agent becomes a “virtual assistant” - and they do a great job. Per the Ikea scenario mentioned in Part 1, the knowledge admin can load keywords and phrases of features customers are looking for and then have the virtual assistant guide them through a browsing or search experience to find the product that fits their prospects needs.

For example, if you have a garden shop, you can create a hierarchy of plant types and their associated keywords such a "drought resistant", "winter flowers", "shady garden,” and other phrases that a novice or expert may use in their search for plants.

Once a solution is suggested, Buy links or Chat buttons can be added to the solution for conversion or have a live agent close the sale. If you’re really fancy, add a click-to-call button for customers to request a call back. 

Next Time

We’ll cover some real world scenarios for virtual agents and assistants. Have a great week!

Let's Talk About Virtual Agents and Assistants (Part 1) by Jon Meyer Meyer

...Aaaand We’re Back

Happy New Year! I hope you all had a great and safe holiday season. I did...which turned my weekly-blog into a monthly-blog in December. Oh, friends and family, you so crazy!

So let’s get back to it.

If you work in customer service, you undoubtedly get a 3-1000 webinar invites a week for the latest tools, how to improve, etc., etc. It wasn’t until the past couple of years that I saw real uptick in virtual agent (aka vAgents, chat bots) pitches. This isn’t new technology as I have used two different platforms over the past 10 years with great success and some admissions of things that could have been done better. So I’m going to try and explain what they are and what the best scenarios are for your self-service objectives.

What is a Virtual Agent?

A virtual agent (vAgent) is basically a natural language search knowledge base in the form of a chat window (hence ‘chat bot’). These are the predecessors of Apple’s SIRI as they do the exact same thing: answer a question just as a person would.  So, yes, they are designed to be somewhat of an artificial intelligence (AI), but pretty far from Samantha. If you read this old Bloomberg article, you’d think that we’d have vAgent’s rattling down call center aisles terminating staff with their own high powered Nerf® guns - but that simply isn’t the case. 

What vAgents do really, really well is that they can convey a customer friendly support experience beyond a giant search box with bulleted FAQ links floating around it. It’s more a guide to a solution than a list of results. Also, the chat format encourages people to type sentences of their queries rather than abbreviated keywords or phrases - which can help with first contact resolution (FCR) by having more detailed keywords and phrase strings.

Some companies go the anthropomorphic route with ‘personalities’ that give the user a more personal experience. Such as Ikea’s Anna:

However, most companies today simply call them virtual agents/assistants so customers don’t confuse them with real people (as I have seen many times in the ones I've administered). Some examples to play with are Coca-Cola, Lenovo, Snapfish, and Autodesk.

There are quite a few players in the vAgent space now, and some popular companies that offer virtual agents are:

How Do They Work?

I have to be careful here, so I’ll keep it very high level on the real nuts and bolts. Basically, the customer experience works similar to a human chat agent: a customer initiates a session that includes one or more questions and responses that will hopefully deliver a correct answer. If the vAgent fails to answer the question(s), then an escalation path is offered to a live agent channel. 

Because they use natural language search (NLS), that means the secret sauce of a vAgent’s success is how well vAgent’s ‘vocabulary’ and ‘voice’ is programmed by the admin to return the proper response. It sounds a lot like knowledge base parameters, but this differs with phrases and omission words are also factored in. 

Here’s an end to end example:  a customer goes to a furniture store’s website and asks, “I want a chocolate davenport”, even a well programmed KB will likely return a null result unless that terminology is in the article and the keyword algorithm has the option to weight words or terms that are attached to synonyms.

vAgents have CSAT correlations to sessions (or conversations) where user input data is harvested for successful and failed sessions. This data harvest/correlation can be used to see what user phrases were used in unsuccessful conversations and likely escalated to a live agent. So a great vAgent admin will see unsuccessful or escalated sessions, review the conversation, and realize that the customer was looking for a “brown couch”. From there, they will add that phrase or key words into a synonym list (“Brown = chocolate, coffee, espresso”, “couch = davenport, sofa”) and omit the unimportant words (“I” “want” “a”). The admin may also have the option for keyword tweaking so certain words (and their attached solutions) will be pushed higher or lower in the results. 

Phew. Give me a second to wipe this trickle of blood from my nose after navigating how these things work without telling *exactly* how they work. 

To expand on their analytics, this type of tool has to have very powerful and detailed information to ensure CSAT. As mentioned above, trending of searches, clicks, navigation, promotions, session completion and abandons, searches, and much more. They are a data junky's dream in a tight little package that can handle unlimited customers at a time (concurrency).

For Part Two, I'll address use cases, scenarios, and KPIs.

What Is Self-Service? by Jon Meyer Meyer

Hello and welcome to my first post :) I'm hoping to churn one of these out a week as long as I have ideas to contribute. It's been a while since I have written a blog, so everything will be a bit dry at first, but hoping to switch from drinking tea with my pinky out and upgrade to my light-absorbing, high octane coffee. Also, despite the title of this entry, I'll touch on what I have learned (and continue to do so) in my career and how each facet of the Contact Center has touched community, knowledge content, and social media. That said, if you want to know more about me, check out the About Me page just to show you all it's not 100% crazy talk.

So, Self-Service...

Briefly: self-service is allowing a customer to easily resolve a solution without directly connecting with your company's busy staff.  (I know, it sounds like I'm advocating the killing of the "personal touch" and "customer engagement", etc.)

Self-service can happen through a virtual agent (chat bot), knowledge base, static pages, FAQs, blogs, telephone IVRs, and even social media and community. Basically, if the information can be retrieved through browsing or searching without reaching a human, the customer has been self-served. The price of self-service is also far, far less expensive than even email (hundreds of time less in some cases).

Not to put my experiences on a pedestal, but self-service is a bit more complicated than many people believe. It's more than just a search box and some article links. Like any good site, it's a journey - a balance of customer satisfaction, quality content, and escalating quickly when that content isn't sufficient, and then filling those knowledge gaps to improve the site. A frictionless experience.

"But Customers Love to Call!"

Well, that really depends on a lot of things. Yes, if you place your phone number in a light box over your support site, people will call. If you hide that phone number and force people through an infinite loop of self-service (that dark side of the Self-service Force), then, hey, people seemingly can't get enough self-service - just look at those page usage metrics and the reduction of calls!

It also depends on your industry and company mandate. If you are a financial institution, then yes, it can be argued that a phone number should be easy to find - people tend to get antsy when asking about money and generally don't like jumping through flaming hoops like a poodle covered in the gasoline. However, an industry with more complicated questions, like software, may want to up their self-service with a robust knowledge search for all those crazy error codes when trying to install Windows 8.1 on their IBM ThinkPad. If there's a clear article that's well formatted and easy to understand, where the customer feels empowered to try it themselves, that's great for not only the customer, but the agent has more information of what the customer has tried and bolsters the resolution dialogue if they should call/chat/email.

As for the company mandate: are you a warm and fuzzy company like Zappos or a bit more austere like Microsoft? That's a huge part of the support customer journey and the offered support channel priorities as well. Zappos, who is centered on taking the stress of our buying shoes online, offers all channels evenly. Microsoft, on the other hand, wants to ask you a survey about their support before even using their services. But because of their size, customer base, and product lines, they have a heavy self-service presence and login requirement to reach an agent.

Microsoft's survey request on entering their Support Center, which has seen major improvements over the years.


A strong self-service experience not only helps your customers, but your support staff. Many customers, indeed, just want to call (any Support conference or webinar will have research on who calls, why, etc). Having a well curated knowledge resource speeds up handle time for agents/staff and generates SEO to enhance the frictionless support experience.

So Is This the 'Crazy Talk' Part?

For some readers: absolutely.

I have been working with self-service for almost a decade and a half and I've seen quite a bit from an execution level (do you really want an FAQ under that search bar?), platforms (do you even SEO, brah?), and people (Your natural language wizardry is trying to replace *people*! Will no one think of the CHILDREN?!). Surprisingly, the answer to all those parenthetical questions are equally "yes" and "no" depending on the problems that need to be solved. 

What I am getting at is that each company will handle Self-Service in their own way to accommodate budget, add value, teach, and most importantly, keep your customers happy and retain them. For example, financial institutions, software (especially SaaS), and retail will all have varying sizes of public/internal knowledge to resolve customers questions. The size of the company - start-up, SMB, and large businesses - will determine the scale and magnitude of the knowledge needed (geo-location, languages, portals, etc) as well the resources need to accommodate customer help demand. Throw B2B or B2C into the mix (many companies have both), and customers finding solutions on their own gets pretty hairy very quickly. I apologize for the hirsute visuals. Ugh.

So, let's leave it there for now and chew on it. The point of this blog isn't to solve everything in one post but to start the solution cycle for the next app tycoon writing code with his pal in a pile of Diet Dr. Pepper cans to the established company faced with infinite choices of how to serve their customers. I hope I have done a decent job of laying down that first layer for many great discussions and posts to come.

Let's talk soon and feel free to share your ideas/comments in the comments.