Text Analysis and Cutting Edge Customer Support
In recent years, Support functions particularly at SaaS companies have transformed from costly must haves to revenue securing and generating need to haves. Customer Support and Customer Success now contribute directly to company revenue through increasing sales and upgrades and, most importantly for SaaS companies in growth mode, by reducing churn.
What does good customer service look like?
According to a recent survey carried out by Zendesk, customers hold speed of response and speed of resolution in the highest regard when evaluating a customer support service.
As customers we have become needier, we expect immediate responses from service providers and overall we have become more open to using multiple channels for support queries other than the phone. We tweet about our frustrations of services going down, we email about account queries, we use chat boxes for immediate responses and we provide feedback through form submissions. SaaS companies for example, rely on their support functions to provide personal, timely and cost efficient support to their customer base where and when their customers want it.
It’s not only the SaaS industry which has seen a shift in how much it relies on Customer Support. The same can be seen in the e-commerce and online retail industries. Companies like Zappos pride themselves on Customer Support and have successfully positioned it as a differentiator over their competitors.
Good customer service is speedy, focused on customer success and personalized.
Traditionally customer support was done over the phone, which often meant sitting on the end of the line on hold, only to speak to someone who would route you half way round the world and back again to even take a note of your request and log a ticket. Today things are different.
We have become more digitally inclined in how we interact with service or product providers and I know from my own experience that picking up the phone to call support is often a fallback for me. It’s pretty much the last thing I will do to try and resolve a problem. It’s what I will do after I have exhausted every other channel, self-service, chat, email even social media channels, looking for an answer to my query.
This has only made it more difficult for companies to stay on top of customer queries. In order to provide a seamless and efficient experience, support functions need to meet customers where they are and provide the same level of service across every channel being personalized, efficient and informative.
The shift towards a multi-channel support function has meant organisations have had to adapt to increase efficiencies and lower costs by adopting streamlined processes and procedures often through the introduction of technology. The growth of Zendesk, RightNow and Intercom in recent years, companies focused on customer interaction and support, highlights the fact that organizations are investing more in their support functions and are moving from traditional support offerings to more technology driven processes to provide less costly, more efficient and more intelligent processes.
Apart from phone support other common channels for customer support rely heavily on textual interactions, whether it’s email, social, chat or form submissions customers are interacting with service providers by communicating with text.
How can we leverage the large volumes of text gathered in support interactions?
Analyzing the text of an email can provide insight into the context, intent and sentiment of a customer’s query. Being able to automatically route account queries to accounts, support requests to support and sales queries to a sales rep not just improves efficiencies, but also makes the interaction easier and more enjoyable for the customer.
Keeping on top of all comments, tweets and shares on social channels can be pretty difficult and some comments or interactions often need immediate and personalized attention, especially those left by frustrated or disgruntled customers. By analyzing tweets and comments, you can automatically determine which interactions are support queries, frustrations or even compliments about your product or service, allowing you to action them appropriately.
Free form submissions are a great way to gather customer feedback or even customer support queries. While they provide a method for customers to leave feedback, making sense of free form submissions can be quite difficult. They gather a lot of noise (useless submissions) and are for the most part unstructured which makes them difficult to search and report on. Having to manually trawl through, classify and monitor form submissions is extremely time-consuming and costly. As a result, they are often ignored and overlooked when they may hold extremely useful business insights.
By analyzing text, extracting keywords, entities, intent and determining the sentiment of a query, whether it is an email, chat, social comment or form submission you can effectively deal with customer queries and increase the productivity of support functions. Text analysis and natural language processing advancements allow support functions to be more consistent, timely and even personalized without losing efficiency.