Marie: Tell us a little bit about Infogain, what are your areas of expertise and your background with customer support and knowledge management.
Randy: Infogain is a global consulting and software engineering company focused on technology and digital transformation services, with 4,000 employees worldwide. We have a long history of expertise in CRM, Call Center and the integration of Knowledge Systems. The Knowledge Practice spans across our vertical markets which include high-tech, insurance, healthcare and the travel and hospitality industries. Our expertise lies in delivering front-end, customer-facing technologies, processes and applications, leading to a more efficient and streamlined customer experience
Marie: How does intelligent search fit into Infogain’s vision for the call center of the future?
Randy: If I was to think back fifteen years ago I was scared of ‘big brother’ finding out anything about me. Now I, and millions of others, have moved to the other end of the spectrum. I expect that companies know as much about me as possible, and provide me with precise, focused contextual knowledge, each and every time.
This means that Enterprise Knowledge systems not only need to be self-learning and self-tuning, which means knowing the best content to serve up at the most opportune time, but it must also be modified and filtered by everything you know about my context to provide the best customer service experience.
My context can include many factors such as geo-location, point of entry into a system, groups and roles in which I have membership, my purchases and travel history, my preferences, and the path I have travelled through a website before my interaction with your company.
If you think about these concepts, the travel and hospitality industry looms with massive potential. But whichever the industry, you need an intelligence engine to ingest and learn from all the interactions of your customers, and inject relevant, contextual knowledge in the flow of the user.
Imagine a casino that knows all of your favorite artists, games you play, what you drink, who your friends are and the purpose of your visit, etc. They are then easily able to match up content, offers and up/cross sells to your exact needs, and ultimately – their own.
I travel constantly. Companies know massive amounts of detailed information about my preferences and travel history, but this information is rarely or poorly used. As a case in point; I was recently in Cabo San Lucas, Mexico on vacation in an area known as the Marina District. It is a major tourist area. I am sure that I had the exact same 50 questions and needs that 10 million other tourists have about services, rates, maps and reviews. Even though my search engines had my exact geo location and history they served up absolutely nothing useful. There was no understanding of the “intent” of things that I needed.
In a corporate example, the driving force for implementing intelligent search is call deflection. The technology allows corporations to be so intuitive and responsive, according to their visitor’s context, that their needs can be met without a call center interaction. It can also mean that a Tier 1 agent equipped with the same swift access to contextual answers is able to rapidly, and with a high level of success, resolve issues on the first call.
Marie: You’re absolutely right. What, in your opinion, are the key capabilities of an Intelligent Search solution that make this possible?
Randy: There are eight critical factors that I feel are must-haves in an intelligent search solution. If any of these are missing, success will be limited.
1) There must be a unified index. This means that information can be pulled together from many different sources into a single index. This is a critical piece to be able to leverage enterprise-wide knowledge.
2) There must be a strong integration capability with multiple types of systems through APIs and WebServices. You need to be able to surface the information when and where your employees, customers or partners need it.
3) The system must be self-learning. Based on the last 1000 similar searches it must know and optimize all of the articles that are actually solving problems and successfully deflecting similar cases.
4) It must be able to pass complex contextual strings of information about the visitor to create a personalized experience. Think about your different types of users coming to your self-service site – customers and their unique profiles, partners, prospects – and how different their needs are. There is no way a one-size fits all experience can help all of these members succeed at self-service.
5) It needs to support complex security models so that you only show content your visitor is allowed to see. Your intelligent search solution needs to respect the security permissions of each of the systems it’s indexing, so only the results that this specific user would get from performing a search in this very system are returned.
6) There must be the ability to rapidly index large amounts of content.
7) Custom, in-depth reporting needs to be available. Out-of-the-box analytics are unlikely to satisfy a wide range of business analyst queries.
8) The search engine must be able to understand visitor intent. If, for example, your visitor is searching for a red Honda, his/her intent is to buy a car. Intelligent search not only delivers results for a red Honda but also delivers options for financing and local dealer information.
Marie: Self-service success and case deflection are hot topics in the industry, and for good reasons. Can you share best practices for injecting intelligence into self-service to make those two things a reality?
Randy: The first step is building a roadmap towards your vision of intelligent self-service. While there are many steps for a complete roadmap here are the critical ones to start with:
- As a company, you must collectively decide on the support experience you want to deliver across all channels. This means that your self-service strategy can not be planned separately from your assisted support delivery. They are all part of the same experience and therefore must be planned together for the best outcome.
- Identify all of your content sources and decide what valuable information your customers, employees and partners need access to.
- Identify one or two high value systems of interactions where you want the knowledge to be surfaced. Likely, the most valuable initial candidate is your CRM system for your employees, and your self-service site for your customers. Known customer and product information can easily be concatenated into highly contextual search strings.
- Create a requirements document based on the capabilities highlighted earlier and the specific needs of your organization.
- Match up the requirements against vendor capabilities.
For more information on how your organization can benefit from intelligent search, improve customer service and reduce case volume, download this guide to Case Deflection and Self-Service Success.