Mark Floisand on Coveo’s Position in Gartner MQ for Insight Engines

By Gabriella Pirrone

August 31, 2018

AI, big data, Cloud, Coveo, data, Data Security, Elasticsearch, Enterprise Search Market, Exclusive Interviews, gartner, on-premise, Press Release

For the second year in a row, Gartner has released their 2018 Magic Quadrant for Insight Engines report profiling 13 vendors and their key differentiators, showing who embraces the Insight Engines augmented search technology with artificial intelligence to deliver insights.

Gartner predicts that by 2019: "50% of analytic queries will be generated using search, natural-language processing, voice or autogeneration" and "by 2022, information will proactively find more employees more often, thereby providing the insight needed to progress decisions and actions, and reducing reactive searching by 20%."

In the report, Coveo was yet again positioned as a leader since its inception and also received a huge commendation from Gartner by being positioned furthest on the completeness of vision axis, which the company believes is due to its massive commitment to R&D.

"Coveo's position in the Leaders quadrant reflects a comprehensive vision, as demonstrated by its market understanding and sales strategy, together with strong execution founded on its product, operations and customer experience."

To hear more about Coveo’s commitment to R&D, what has contributed to their success in Gartner's positioning and how they help many businesses and digital leaders achieve results, I reached out to Mark Floisand, Coveo’s CMO. Be sure to follow along below to read our exclusive interview.

In your press release it mentions “Coveo is positioned again furthest on the completeness of vision axis, which the company believes is due to its massive commitment to R&D” Where has your focus been in R&D that has contributed to this and what is your focus and commitment moving forward? 

"Over the years Coveo has built up teams focused on our Cloud infrastructure, our core indexing, connectors and query capabilities, as well as our analytics and integrations into Salesforce, Microsoft Dynamics 365, Sitecore and more. However, a few years back we began investing heavily in recruiting a deep machine learning research bench, and this has fueled our ability to help our enterprise customers predict what their customers, partners and employees need next.

We continue to invest heavily in our R&D team, which represents nearly 40% of the employees at Coveo. We’ve been hiring aggressively – and continue to do so – so please tell your friends! Our Montreal office alone has expanded to 70 people, having only opened 2 years ago."

Where do you see the most value for artificial intelligence in search?

"Search is a process of going and finding information. It requires people to actively request something, then filter and iterate until they have what they think is the best answer. We believe that model is fundamentally out of date. People should expect proactive recommendations – suggestions, ideas, content, products – that anticipate what they’re most likely to need next, and offer it up to them. AI-powered search and recommendations – or insights – use all the data about what content people have interacted with, what interactions they’ve had individually and in aggregate, and predict from that data what they need. All in real time."

The report states “Coveo's emphasis on factoring search usage into relevancy calculations has brought it success with self-service use cases in the fields of digital commerce and customer- and employee-facing support.” Can you go a little bit more in depth on those and any other interesting use cases you’ve come across?

"Being relevant at every interaction an enterprise has with its stakeholders, has measurable benefits to the strategic aims of the company:

• On an ecommerce store, browsers convert into buyers when they’re presented with engaging, relevant offers, which directly drives growth--and it’s binary: they either convert or abandon; so offer them the most relevant shopping experience to help them through to the transaction.

• Customers are happier when they can self-service and discover what they really need, themselves – which drives up CSAT, lowers support costs by reducing the volume of repeat calls into agents, and increases lifetime value (LTV).

• Employees are happier when they develop knowledge to become more proficient in their roles, and they have the most relevant information for the task at hand offered up to them. This reduces employee churn, grows the talent pool, and aids organizational learning."

The report states “Although Coveo offers both on-premises and cloud products, its focus is cloud-based deployment. Its machine learning capabilities, for instance, are cloud-based. This may deter organizations unwilling or unable to accept such a delivery model due to security or other concerns about third-party processing of data.” How will you address organizations unwilling or unable to accept a cloud-based model due to security?

"Coveo offers a hybrid deployment model, specifically for customers who may have those concerns. Yes, we can host our enterprise customers’ entire Coveo instance ourselves in our HIPAA-compliant, SOC II-compliant cloud; or they can choose to host the search index within their own on-premises or private cloud infrastructure. We use Elasticsearch as the core index technology in this model, which allows enterprises to maintain their own Elasticsearch index in an environment they are in control of; we add our analytics and machine learning capability as a service layer on top of that index, which we run from our Coveo Cloud. This hybrid approach works well, and is ideal for customers that have the desire and ability to maintain their own Elasticsearch environment, but want to benefit from Coveo’s advanced AI-powered search and recommendations on top."

Gartner explains that "Insight engines apply relevancy methods to describe, discover, organize and analyze data. This allows existing or synthesized information to be delivered proactively or interactively, and in the context of digital workers, customers or constituents at timely business moments." So essentially, insight engines are the next generation of enterprise search solutions and as organizations collect more data, cloud solutions have emerged as cost-effective, highly scalable alternatives for data storage and processing.

In my opinion, I think we will expect to see increasing interest and adoption of these cloud-based search/ insight engines in the enterprise world. 

Ending Notes

With Coveo also being named a leader in the 2017 Forrester Wave report for Cognitive Search and Knowledge Discovery Solutions,  Forrester actually conducted a study to show as many as "72% of customers prefer to use self-help options rather than reach out to a company, as modern customers tend to be self-researchers." It means that consumers are searching your website for more information to get answers to their questions, long before they create contact with sales or a support department.

During my interview with Mark, he made a really good point with stating “Customers are happier when they can self-service and discover what they really need, themselves” in my opinion, and now a days being surrounded by a millennial-dominated workforce, they (or I in this case) have a lower tolerance for hassle and would rather expect a quick answer to what I’m looking for instead of a massive page of content that links out to pages and pages of results.

 

Gabriella Pirrone

Gabriella is the Digital Marketing Assistant for CMSC Media. She brings a wealth of knowledge from not only a CMS perspective but also content, SEO and eCommerce. She enjoys everything social media and staying ontop of the latest trends in the digital marketing world.