Search has changed the way customer service is offered and provided. Smarter algorithms and better machine learning models can help deflect cases, but sometimes a call is necessary. Search can increase the ability of responders to resolve customer concerns. Platforms like Coveo are doing a phenomenal job leveraging search to empower customer service representatives with relevant, often protected or sensitive information.
For customer portal applications, rapidly producing and securely managing sensitive content is the name of the game. One of the biggest challenges implementing search is guaranteeing that a customer’s sensitive data is not available to non trusted users. Handshake makes mapping this security simple, irrespective of where it’s stored..
When someone calls a help line, a timer starts. The Customer Service Representative seeks to resolve the member’s complaint as quickly and efficiently as possible. More and more frequently, CSR tools are built using a search platforms such as Coveo or Watson Explorer. These systems learn over time the most direct method to resolution. However, without relevant content readily available to the search, the CSR and the algorithm are at a loss to access critical information to resolve a case.
This content can come from a myriad of sources, usually some combination of web content and ECM content (think IBM FileNet P8, Alfresco, Documentum). Here, indexed content needs the right metadata and highlighted content to quickly point the representative to relevant data. Connectors are the key to getting that information to the search engine and the CSR.
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When a member logs in to your portal, they have an agenda. Where is my bill, what is my copay, is this covered? The user knows what they need, but you might not. Good site design only goes so far. Many organizations now turn to search correct for this. Typically, evidence of a transaction is stored in one system, records in another, member details in a third. Handshake helps ensure that this content is securely indexed, guaranteeing that results are only those accessible to the logged in member. Connectors let you abstract these controls when indexing content from various sources. One less thing to worry about, one thousand more things available to the user.
Many companies use solutions like JIRA and Github to manage tickets and product enhancements. Development teams are able to communicate status and devise new features based on requests from user communities. Tickets are rapidly created, edited, and closed. Companies spend considerable resources to keep these up to date and resolved quickly. As such, it’s imperative that the search solution is returning the most relevant tickets to a user’s queries. Search results should favor resolutions and high impact, low complexity fixes. Users prefer to click on a “resolved” ticket to an in progress one. Connecting the ticketing system to search, with transformations to boost the more relevant responses, guarantees that relevance is never out of sync with queries.
Enterprise Search is the hardest use case to quantify in terms of ROI, but the most transformative for internal policy. Over the years of doing e-business, every enterprise ends up with data scattered across many content management systems. Sometimes there is a good reason for these silos, (regulatory requirements, types of assets incompatible between different systems) sometimes the chaos the result of shifting priorities and rapidly changing technology, compounded over years. This leaves content spread around the company, metadata in complete disarray, and overall confusion for the employee. Whatever the reason, not having all your enterprise content in one location can be an Achilles heel for knowledge workers. It can slow down or block employees’ ability to find the content they need to do their job. Search is often the answer, provided you are able to index from your ECM systems. That’s where Handshake comes in.
Standardized metadata and content enabled search let knowledge workers find the content they need, regardless of where it’s stored. Use cases include exploratory (what do we have on topic A?) and targeted (I need everything related to this employee) searches. Effective Enterprise Search needs all the content, regardless of storage, which was one of the biggest problems that we build Handshake to solve. Our team has been working in the ECM space for almost 30 years and know these struggles too well. Regardless of how niche your ECM solution may be, we can build you a connector.
Search Adjacent Use Cases
Over time, between developing Handshake and engaging in Migration projects, we’ve identified other use cases for Handshake besides simply connecting ECM sources to Search targets. Handshake is fast and extensible, so we asked ourselves, what else could we use this technology for? Handshake is great at reading and standardizing content before sending it anywhere that can accept REST protocols, opening the door to a number of solutions.
Content Back up
Many companies are required to store back ups of content. In the current landscape, hyper focused utilities or scripts will copy, package, and move content to a longer access storage device or platform. Handshake can do this, too, with none of the custom development. Just point to a storage target and set the traversal type.
When sunsetting a legacy application, the question is always how. We have an entire team dedicated to large scale migrations, but sometimes a connector can do the job.
Legal Hold Requests
Connectors to StoredIQ and Exterro as targets are in our pipeline, but being able to find content relevant to a hold request is crucial to avoid lawsuits.
Any that we missed?
We are actively developing this platform to be the best it can be. If you have a more niche use case for search connectors, we’d love to hear about it. Reach out to firstname.lastname@example.org and see what Handshake can do for you.