The relationship building with the entire team at LMI from Sales, to the Account Manager to our Customer Relationship manager and their product Bold360 was excellent. They were always willing to listen to different ideas and try to make them work for us
It's easy for anyone who is expecting some simple AI problems like fetching the keywords, understanding the intent, language translation, etc. to be solved from an existing database and all they need is to connect to their APIs via a subscription model. But for complex use cases, there is still room for improvement like customization of underlying AI models for a specific use case like identifying some unique identifiers with respect to industry.
Reporting capabilities. I think the dashboard and reporting tool could contain more details in terms of what data is visible and available to the user/administrator.
Native mobile applications to provide added support.
Improving the beta testing program to use new features before understanding whether the update can be pushed out without causing issues with the end-user.
Day-to-day use of Bold360 AI (chatbot) use (reviewing new questions, adding new responses, tagging, etc.) is fairly simple, but utilizing more advanced features and custom channeling, etc. typically require escalation to developers and may require additional costs if you want help to implement
Great customer support management provided by LogMeIn, which gives you a direct line with regular meetings with the company to make sure your implementation is a success. [The] account manager is always readily available as well for engagement. Opportunities though exist in a balance between professional services support and VIP support that can be improved upon more.
I used LivePerson in my previous company. It was the same as BoldChat in terms of being a standalone chat application. But when I started using Bold360, for the very first time I felt I'd found a tool that made chat a really good channel for communications.
IBM Watson Assistant has been early into this market and has improved a lot over time compared to Azure AI Cortana. More documentation related to the services. But Ease of integration Azure AI ranks over IBM Watson Assistant. And again in terms of services offered under the ecosystem, Azure AI precedes IBM Watson Assitant.
Considerable saving on ticket deflection so return on investment
Saved on extra support engineer recruitment through self service
Enabled support engineers to concentrate on more complex customer issues as simple and semi-complex issues are generally dealt with through self service--so better quality of service for customers
Difficult to ascertain the ROI as we are a software house who have developed a module in our application using Cortana. However for companies that use our software I would say the use of sentiment analysis in our application could free up at least 1 full time resource to be used elsewhere in their organisation.
