Can a Searchbot Solve Low Employee Adoption of ITSM Portals?
Google algorithms provide excellent search results because of the vast amounts of rich and targeted data that Google has access to. Unlike the World Wide Web, however, enterprise service portals are limited in the number and type of articles that they host. That has historically been a challenge for self-service portals that try to leverage “Google-like” algorithms to provide answers to employee questions.
When employees search on portals, they get a voluminous listing of results that may or may not contain the answers they are looking for. If they do manage to find a relevant topic, it is often either outdated, too technical, or not specific enough to their situation to be of value. The result is not just that they give up and simply call the help desk, which they do, but also that the next time they have a question they don’t even bother looking in the knowledge base.
More recently, searchbots have been introduced that attempt to solve the poor adoption of self-service portals. The underlying challenge is that the same knowledge articles are being used by these searchbots, and therefore are not addressing the core of the problem—employees have already voted against the knowledge base experience.
So why do vendors believe that putting a chatbot on top of a portal is going to provide a solution to the problem of employee adoption?
The Problems with Google-Like Searchbots
The reasons a Google-like algorithm will not help employees get better search results are two-fold.
First, a better search will not solve the issue of employee language. Consider how many different ways there are to ask the same question, such as “what is the guest WIFI name?” Employees could search on the network SSID, guest net, wireless connection, and the list goes on.
For a search to be effective, the employee has to search on the specific key words in the article they are looking for, without knowing in advance which words those are. To add complexity, since multiple people are likely writing individual articles, there is no guarantee the same words are being used across all articles on a single subject. This means your employees cannot use their own language, and simply doing a better job of searching on specific key words won’t help.
The second issue has to do with the limitations of the knowledge base itself:
- Content is missing. Service desk agents are generally graded on the rate at which they close tickets, not on the number or quality of the knowledge base articles that they create.
- Knowledge base articles are out of date. Once created, articles are rarely updated and will quickly become stale. Take for instance the new iPhone XS. It was recently launched by Apple, and it is possible that a number of employees are looking for information on how to upgrade, whether they should, etc. By the time an article has been published, the trend has shifted to the newer iPhone XR.
- The articles are long and complex. Knowledge base articles are generally written by service agents, to help other service agents get up to speed on a topic so they quickly close tickets. They often contain a great deal of technical information, acronyms, and other content that employees outside of IT are not familiar with. This means that for many employees, even if they find the right articles with the answers they need, they may not understand them.
This is why doing a Google-like search on knowledge bases is generally not effective.
A New Approach
Espressive Barista takes a different approach. Rather than search for key words in your knowledge base articles, Barista takes advantage of our unique Employee Language Cloud. The Employee Language Cloud was purpose-built to redefine how employees get help. Barista comes out of the box with the ability to understand over 15 million different things. Barista does not search on key words, but instead understands the context of what is being asked to provide a meaningful response. When employees ask a question, they get a clear, direct, and highly personalized answer.
If Barista does not know the answer to an employee’s question, then Barista does several things. First, Barista leverages the Employee Language Cloud to understand the context of the question to connect the employee with the person best suited to solve the issue. So, if the employee is having a problem with the network, then the question will go to a network specialist and not just anyone in IT. Tax withholding questions will go to payroll, not HR. It is not good enough to simply create a ticket. Employees must be connected to the right person, the first time.
Barista also fully populates service tickets, relieving both service desk agents and employees from the data entry burden of standard ITSM solutions. This delivers the benefits of a ticketing system, such as the ability to track issues and follow problems to resolution, but without all of the drawbacks such as the impersonal nature of ticketing and the extreme amount of data entry required.
The other, and perhaps more important, thing that Barista can do is to learn from every interaction. Barista gets smarter based upon the response that the service agent provides. This way the next time someone asks a similar question, Barista will know the answer. And isn’t that better than writing another knowledge base article for people to search on?
See how Barista can give your employees the answers they need by requesting a demo.