Throughout my career, I have witnessed all sorts of attempts to lighten the load on call centers through various ways of optimizing or automating the care process. Even when they are set on “solving to sell”, call centers remain cost centers. If you are successful at reducing the Average Call Handle Time (AHT) by improving call agent’s efficiency or allowing your Customer Service Representatives (CSRs) to handle several conversations at once with a tool like Chat, you will reduce costs substantially but savings will eventually plateau.
It is therefore no surprise that the Holy Grail of Care organizations has been to attempt to simulate agent interactions for the past 15 years.
Initial attempts to surface knowledge bases on websites in FAQ sections were mostly met with disengagement and contempt by customers; More often than not, they failed to address the specific issue the customer was having, and had little or no understanding of context. More importantly, a majority of customers couldn’t find them because they were buried deep into the website or, simply, because they were too overwhelming.
We then saw the emergence of the first chat bots. The first generation was too simplistic and led to a lot of frustration with customers who were faced with systems that didn’t understand questions and only had the ability to handle very trivial issues and dialog.
We’re now in 2022 and if you look at your digital care interactions,
you can ask yourself “what’s happened?”
It’s not to say that digital care tools have not improved – they have – but there is still a disconnect between what we would like them to be and what they deliver.
Not every system uses Natural language Processing (NLP) and when they do the intelligence behind it still does not seem to resolve complex issues. Rare are the all-encompassing systems that understand the customer utterance in the foreground, deliver a thoughtful and flexible customer experience and connect to data sources in the background to gather the required context for efficient troubleshooting. Juggernauts such as IBM, Google and Amazon (although Amazon Connect more focused on the call center functionality itself) have entered the arena with very powerful NLP to understand intent and the ability to create workflows through powerful UIs but they typically offer open, highly customized systems that require entire teams maintaining and understanding them: instead of owning a specialized tool to handle digital care and experience, you own pieces of a technology stack and still have to build the solution, the integrations and the Customer Experience (CX) yourself.
Instead of owning a specialized tool to handle digital care and experience, you own pieces of a technology stack and still have to build the solution, the integrations and the Customer Experience (CX) yourself.
Sweepr is a Digital Experience Platform that contains all the pieces to handle your digital care needs. Used as a standalone tool, it excels at solving complex customer issues while providing outstanding CX. It comes with:
- Its own flexible NLP to understand customer intent
- A low-code tooling environment to easily create workflows and link them to intelligent decisioning
- Artificial Intelligence and Machine Learning (AI/ML) capabilities to decide on the best possible resolution and feed analytics back into decisions
- Integrations to diagnostic tools and backend data systems to personalize the interaction at a granular level
- Creation of workflows is tightly coupled with the creation of the experience so you are designing a top of the line CX for your customers across multiple channels
- Powerful analytics to understand where to optimize the digital journeys and to detect directional data signals
Companies who have an overarching strategic goal and investment to leverage intent discovery across digital channels and call center might have already been using the aforementioned solutions from IBM, Google and Amazon as well as more niche bot technologies. Sweepr can, in those cases, be used in tandem with these solutions and bring added value by going into the more complex interaction space. Looking at Google for example and their CCAI product, the two solutions can be extremely complementary:
- Interactions such as automated First Call questions related to knowledge base articles and live Agent chat can be handled by CCAI
- CCAI is strong on Intent matching which can be used to feed Sweepr with more granular understanding of the issue at hand
- Sweepr’s Use cases are focused on more detailed, context-rich and personalized interactions. You will be able to deploy and manage them without embarking on a long and expensive IT project.
- Sweepr can support the creation of a deeper, more complex and personalized set of interactions that can be closely bound to CCAI
- Sweepr’s analytics and insights can be fed back to CCAI for a better understanding of future requests
- Sweepr can provide CSRs with a full and clear view of the the digital experience a calling customer went through and help CCAI make the routing decision to the call center based on that information
In either case, Sweepr can help you achieve your goals by promoting a customer centric approach to digital care while executing on business goals. Contact us for more information.