Why should you use an omnichannel contact center for your customer support line? One of the reasons can be the availability of data containing direct client interactions, all that in a single solution.
The relevant data analysis has a great potential to support data collection on Customer Experience. According to Gartner, by 2020, up to 40% of data analytics projects will relate to an aspect of Customer Experience.
The topic of data analytics and its application is also reflected in today’s topic from a Questions report generated at AnswerThePublic, from which I have chosen “Customer Experience”. The questions circulating on the web clearly indicate that a majority of frequently asked questions come from the professional environment: “How can customer experience create a difference”, “Why customer experience matters”, and in particular “How customer experience drives business growth”.
Gartner’s prediction, which you can find in the link to the relevant article, was published in 2017. In January 2019, it was supplemented with an interesting analysis that identifies threats to evaluating Customer Experience: high costs and hard-to-quantify benefits. Managers who cannot gather clear data on Customer Experience project results are likely to face a potential budget reduction.
Gartner predicts three key tasks to ensure balanced costs of building customer relationships:
An omnichannel contact center enter the Customer Experience data analytics process not only as an effective customer service tool, it also serves as a source of information how customers perceive their service providers.
Most data containing customer communication is available in a considerably unstructured form: e-mail messages containing various disclaimers or historical communication since customers simply responded to the previous message instead of writing a new e-mail. There can be web chat communication and social media where customers communicate under various nicknames.
And then there of course recorded phone calls, the analysis of which is usually limited to the supervisor evaluating randomly selected calls.
Aspects of Customer Experience thus in effect support contact center extension with speech analysis and artificial intelligence systems to analyze non-voice interactions.
This entire complex will make it possible to analyze data from authentic communication with customers and also give businesses a tool to use such data in real time.
This will result in instant customer recognition and allow the creation of highly effective personalized data set – available to the agent at the time of contact – which will not only improve performance indicators but, more importantly, support business goals, in particular cross-selling, up-selling and retention.
What do you think about this topic? Do you plan to analyze data from all communication channels to evaluate Customer Experience?
For a full text of Garnter’s and AnswerThePublic reports that were used to compile this article, click on the links here: