Coveo: A platform for personalized AI-driven search and relevance
Broadly, Coveo enables predictions for customer needs across platforms when it matters most – in real-time.
So it comes as no surprise that it’s trademark search relevance capabilities feature in Gartner’s Magic Quadrant for Insight engines in 2019 for three years running.
What Coveo does for search.
So far, the platform essentially unifies silos for accurate consolidations of information to drive multi-channel continuity of experience. This, in turn, drives search discoverability.
Concurrently, you also get search-friendly Components to lean on with Coveo’s an index agnostic platform.
Search as an opportunity
An active search is much more than idle customer activity.
Altogether, they’ve become something of a living insight into customer buying intent, needs, profile, behavior – all things smart recommendations can springboard from to deliver exceptional experiences.
Meaningful Customer Relationships
Given this, companies can enable scaled, contextual relevance across platforms like Salesforce, Microsoft, ServiceNow, and Sitecore to steer symmetrical operations and buying in the long run. Thereafter, this is paired with transformative personalization and connectivity across all channels and user-bases.
Service as a typical use-case for KB articles
Aside from eCommerce, retail, and storefronts, it isn’t uncommon to see Service Cloud integrations with a knowledge base. Not to mention, it lets support centers access faster query resolution through highly correlated articles strung together as recommendations. This lets agents discover help article in fewer clicks, besides contributing to an article’s weightage through increased viewership.
For one thing, combined with dashboard analytics, insights for queried help articles can be used to publish required articles or resource tools.
Advantages
- Coveo tackles one of the biggest challenges of customer and work experience – search and discovery.
Again, that means time-sensitive search relevance through AI-powered search. Moreover, time-sensitivity extends to opportunities for service and maintenance, product demand snd buying interest, and usage instructions or product knowledge.
- Coveo brings AI-powered search and recommendations to the Salesforce ecosystem, letting developers run wild with implementations that can repurpose key client-data. They can then deliver scaled experiences through a tailored search for both clients and the workforce.
- Enterprises can leverage robust internal knowledge and data to drive the best executive decisions. Data in companies today sits siloed over disparate systems, impeding better search. Coveo unifies this data and accesses it through intelligent search.
- Product interactions can be used to personalize storefront content for users and knowledgebase content for different agents/departments.
- Client-facing teams can get precise profiling and insights for driving sales.
- Support teams can operate beside activity powered search for End-to-end case management.
To complement this, the Case Deflection panel with recommended articles is geared towards the future of service – self-help.
In the meantime, insight panels also give visibility into customer activity as well as relevant resources to help reduce service times, and in turn, client downtime.
- Dashboard analytics and visualizations help executives get ahead of the decision curve with configurable, actionable insights, key trends, and search gaps.
More recent Component additions
Finer behavioral insights with the Lightning User Actions package
Specifically, service and marketing agents can now draw insights from audience interactions from any analytics-generating storefront or even service pages and Lightning Components.
Extended Cloud coverage and usage
At the time, Coveo’s new B2B Commerce experience brings together product catalogs as well as its recommendations, all while handling sensitive pricing through managed user permissions.
Personalized self-service through a new Community Recommendations Component
This is a Component you won’t have to try hard to like.
You can now directly drag-and-drop this Component over any KB page to put up article recommendations on display for visitors. It even shows you the age of the data used for recommendations for monitoring relevance from time to time. All things considered, the fact that you can do that makes the case for combining Lightning Components with relevance engines.
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