The key to meaningful customer interactions is understanding the ‘why’
Article, Marketing Content, 2020
Bill Gates once said that content is king. However, when looking to create compelling customer conversations, it’s really context that’s king.
Now more than ever, customers expect more from their interactions with businesses. Customer engagement is expected to be both personal and efficient. This places increasing demands on overwhelmed support teams (which often reduces customer satisfaction through poor service) while at the same time, business leaders are acknowledging that customers value the experience they have with a company as much as the product or service they receive after purchase.
So how do you go about rectifying this discrepancy?
As it is becoming more difficult and costly for high-growth businesses to sustain human engagement for every single customer query and engagement, automation is becoming more prominent.
However, what many businesses do not realise is that part of the value of introducing automation into your customer support framework is the opportunity it offers to understand exactly why a user is getting in contact at any given stage of the customer journey (yes, we’re talking about the context).
It is possible to utilise this information to inform when, where and most importantly, why these interactions are taking place and thus consistently inform on customer touchpoints and support to improve experience.
That’s why we really, really want to talk about context.
We’re deep-diving into why you should be prioritising the context of customer interactions, making sure you’re leveraging your tech and support framework to improve experience through understanding context, and learning to view the context of customer engagements as data to inform all aspects of your business.
Prioritising conversational context
So what exactly do we mean by conversational context? It’s a fair question considering the reams of data extracted at various points throughout a customer’s journey with a business.
At any given time, there is likely a sales team analysing conversion metrics and sales targets. There’s marketing teams tracking everything from reach and engagement to straight acquisition numbers. Support teams are looking at customer queries, numbers of open tickets and wait times, while businesses overall are scrutinising their existing customer base, targets, markets and ROI.
Amidst all this data and even more coming from external sources (think market research, surveys and competitive analysis), it’s not surprising that many businesses are often overlooking another valuable data point; the actual conversations customers are having directly with their business and why they are having them.
Separate to high-level support team data, we’re talking about context; the specific questions being asked, when and where in the customer journey interactions are taking place, which pages onsite are influencing visitors to engage with chat boxes or other customer service avenues and much, much more. In a nutshell, all of this data is the context in which a person gets in contact with your business.
Only when you recognise the value of context and work to enable your tech to support these interactions, can you truly leverage the real-life engagements users are having on your website and use it for the betterment of your business.
Leveraging tech for context
In the world of customer support, automated software that quickly analyses, greets and supports potential customers in real-time is becoming more appealing. However, some businesses are wary to implement automated software for fear of removing the ‘personal touch’ of a human support team.
But it doesn’t have to be a sacrifice.
'Conversational Relationship Tools' are taking precedence over more basic support software. Not only will tools like this support customer queries, but they interact with users at every stage of the customer journey, using real-time data to intuitively provide users with personalised information and support when they actually need it.
This specific type of automation software is the first step in not only improving customer’s experience by pre-empting any questions or barriers they may have, but naturally reduces the number of queries coming directly to your support team.
These tools also allow insight into the context in which a user is getting in touch, therefore enabling teams to quickly and efficiently answer queries. For example, understanding how a question is being asked, whether a user is still online waiting for an answer or from which web page a customer is getting in touch, will help to quickly understand how urgent a query is and what needs to be done to provide support.
Not only does this improve on wait times, reduce the workloads of in-house support teams and improve overall customer experience, but getting context on conversations can also turn these interactions into usable data to inform and improve on expected future interactions.
Maximising on context through proactive customer support
As support teams are so often bombarded with queries (usually resulting in poor customer satisfaction through long wait times and low-quality interactions), the most logical move is to ease that burden by decreasing the number of queries that come into teams through proactive customer support.
Proactive support is achieved through analysing existing queries and forecasting where in a customer’s journey interactions are taking place. By introducing personalised messages to provide the support commonly required at certain points on the website or during purchase, businesses can solve customer queries before they need to get in direct contact.
By combining proactive support with self-serve information and human interaction, you can dramatically improve customer experience but also vastly reduce the number of queries coming directly to your business.
The funnel can be used by any business by leveraging the context in which many common queries are generated to implement more proactive support earlier in a customer’s journey. This in turn, will allow you to continually improve on your customer support framework.
Using contextual conversations as data
In an environment where the context of every interaction with a business or product is tracked and translated into data, it’s surprising that conversations are often being left out.
In business today, marketers, product managers and sales teams scrutinise the minutiae of business interactions with precision detail. From clicking through to an Instagram page from a paid ad to checking out a blog on the website, these business interactions are used to populate the majority of marketing strategies and overall business plans.
But apart from perusing a website or clicking ‘learn more’ on a paid social ad, as we know customers are also engaging with businesses directly. They’re asking questions and talking to support teams, making them not only leads but invaluable data points.
The context in which proactive interactions are happening with a business is some of the most valuable data that can be ascertained from a potential or existing customer. Not only does it outline barriers a customer may have before purchasing or any disappointment/ confusion about a product or service, but it can also be used to analyse and predict wider patterns around customer behaviour.
Customer messages and queries are not just data to enable support teams to answer as many queries as possible or engage a sales, marketing or product team on how to convert more leads. The context in which a user is contacting your business also works to further inform your customer journey, your support infrastructure and even larger business and marketing strategies.
While support teams will always have their own targets and data uses, contextual data from conversations should be shared across the business but not only that, it should have as much weight in business decisions as marketing, customer and sales data.
Utilising contextual data from customer conversations is a gateway to transforming customer experience through more meaningful and useful interactions. This naturally goes further to improve customer support and encourage business leaders to use this data more intently to achieve wider business objectives.
That’s why we’re all about context right now, and you should be too.