They say that a rising tide lifts all boats, but as Warren Buffet famously quipped: “Only when the tide goes out do you discover who's been swimming naked.” In today’s “low-tide” economic context of rising inflation and widespread layoffs and cost cuts, only agile companies that succeed at delivering a superior customer experience (CX) will survive.
A key driver of CX that often goes overlooked is intelligent enterprise search. Coveo’s second annual Enterprise Tech Report on Search and AI attests to the universal acknowledgments of the importance of intelligent enterprise search. However, it also illustrates a disconnect between the high value of this key functionality and the level of executive sponsorship and prioritization it receives, and it indicates that tech professionals are struggling with enterprise search implementation.
In this article, we explore some findings from the Coveo report, including reasons why AI-enabled enterprise search is important and factors that can make it hard to implement.
The importance of enterprise search
Everyone who uses the internet understands the importance of search: We rely on it to help us find what we need when we need it. Modern search engines can even go beyond simply providing what we asked for; using artificial intelligence and machine learning (AI/ML), they can “understand” our intent and provide suggestions that get closer to what we really are looking for than our initial queries might otherwise have indicated.
It would be tempting to say that search is just as important for the enterprise, but that would actually be an understatement. In fact, search is even more important to the enterprise because beyond finding information and resources, search delivers a whole host of business insights. Search intent can provide detailed information about where your organization is serving your customers well and where you need to take action. Coveo’s report puts it plainly: “People don’t lie to the search box.”
Coveo’s survey of more than 600 tech professionals shows that 84% see high-quality search as being critical to powering digital transformation. Furthermore, 92% of their organizations employ search analytics to drive improvement, with the most important value drivers of search shown in the graph below.
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Value drivers for search analytics (source)
The importance of intelligent (AI-enabled) search
When you use a general-purpose search engine online, you expect it to provide search results from, well, pretty much anything on the worldwide web. The search engine is powerful specifically because it is integrated and covers all (or nearly all) of the internet—you just tell it what you want, and it finds it wherever it may be.
Businesses need this same capability within their enterprises, but it has traditionally been lacking. Each department or unit in an organization performs different functions, so each tends to use its own information management system. Over time, this tends to result in essential business data becoming siloed— separated into many places instead of being integrated into one location. This makes it hard to find information because you need to know not only what information you need but also where it is stored.
Intelligent business search is all about breaking down these siloes. Intelligent enterprise search tools can search many different systems within an organization to provide a seamless experience to all employees who need information stored in any of them. For example, technical support representatives might normally spend most of their time checking information in the company’s technical knowledge base. However, on a particular call, an intelligent enterprise search system might find the necessary information to help the customer in the sales department’s customer relationship management (CRM) system. On another call, it might locate specifications that the tech support agent needs in a product design document within an engineering department database.
Finding the right information at the right time is critical to ensuring customer satisfaction and keeping costs under control, and intelligent enterprise search can make it happen.
Roadblocks to realizing the full potential of enterprise search
While the Coveo report indicates that information professionals clearly understand the value of enterprise search, it also shows the challenges associated with translating potential into motion. Nearly every respondent experienced difficulties in obtaining the support and resources necessary to fully exploit the potential of enterprise search to enhance organizational success.
The issues these professionals are experienced fall broadly into three categories:
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Executive engagement: A full 96% of respondents indicated a disconnect between how important search functionality is and how much executive support and prioritization it received.
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Talent: Nearly all of those surveyed experienced difficulties finding the expertise they need to make use of executive search investments. The most challenging positions to fill include those requiring expertise in data analysis, search analytics, AI/ML, and content/data ingestion.
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Technical challenges: It’s hard to get everyone to agree on anything these days, but 99% of respondents agreed that technical challenges were slowing them down. The biggest areas of concern included systems integration, dealing with high data volumes, data cleaning or indexing, managing unstructured data, and ensuring data security.
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Commonly cited technical challenges with implementing enterprise search (source)
The typical end result of these impediments is that organizations experience delays in their enterprise search deployments. Nearly three in ten (29%) survey respondents said that their system deployments were complicated by multiple issues and significant delays, a figure unchanged from 2021. Only 12% said they considered their projects to be on schedule, down from 15% in 2021.
The need for AI-enabled search
One of the possibly more surprising results from the Coveo report was that 99% of respondents are still tuning their search results manually. There are areas where humans are better than computers, but adjusting search results is not one of them. This represents a huge area of untapped potential—some of the “low-hanging fruit” that businesses are always looking for!
Delivering truly relevant results and personalizing the customer experience is essential for success in today’s business environment. Going beyond customer satisfaction to customer delight is only possible through the deep analysis of data and synthesis of decision-making information provided by Coveo’s Relevance CloudTM Intelligent Search & Recommendation System.
By understanding search intent and learning from the search history of each customer as well as the larger body of users, the intelligent search engine can get so good at predicting what someone is looking for that search can be virtually eliminated altogether.
As a Coveo partner, iTalent has extensive experience in delivering customized, scalable search solutions by leveraging the artificial intelligence and machine learning capabilities of the Coveo platform.
Our full-service team of experts can overcome the technical challenges often associated with the implementation of AI-enabled search. Our deep experience with systems integrations, data management and analytics, data security, business intelligence, and AI/ML ensures flawless and cost-effective search deployments.
To learn more about how we can help your company with its search needs, contact us at search@italentdigital.com.
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