Customer Retention in a Recession - Iterate Quickly with Data Analytics
Charlotte Ward has a tech support career spanning 25 years, and is now Head of Support at Snowplow Analytics. She also has has a blog and podcast, Customer Support Leaders, where she talks with other leaders about all things “support”. Her mission is to build exceptional support experiences that customers will want to tell their friends about.
The overall global economy is expected to shrink 5.2% this year, putting us into the deepest recession since the end of the Second World War.
But there is a silver lining: countries will have the chance to rebuild better.
When we apply this to our industry, the same is true. Many companies have been forced into a digital transformation - one that has helped bring them closer to their customers in our new socially-distanced world.
With this expected 5.2% contraction in global GDP, and the changing buying habits brought about by social distancing/measures to prevent the spread of the virus, customer retention is the most important business objective for 2020.
Now we need to ask ourselves, ‘what will our customers want post-Covid?’. Companies have the chance to build better customer experiences.
Early trends suggest that they want personalized support and fast, complete answers. They appreciate the connection in a time of chaos.
“84% go out of their way to spend more money with a brand that provides great experiences”.
Getting the most out of your data
After our people, data is the single most important asset at our disposal.
Unrestricted access allows us to do 2 very important things:
Predicting your customer’s behaviour is central to maintaining an exceptional customer experience and retaining your customers. That’s rule number one; many companies master this. But you can make all the predictions you like: discovering developing trends as they happen, and adapting to them, is just as important.
The pain for customer service people today is that we often rely on dashboards that are built and maintained by specific stakeholders, meaning we have a restricted view of our operations. It’s hard to dig into the data and cross-reference various dashboards just to find the information that really matters to us. It becomes a real challenge to forecast needs and iterate quickly from a time (and resource) management standpoint.
Conducting analysis through a ticketing system’s native analytical functionality isn’t always easy. It can actually be very difficult to find the views and extract the answers you need in a short space of time.
Imagine trying to see what tickets are most commonly escalated to Tier 2 - and what handling times these tickets have in comparison to the Average Handling Time of Tier 2 as a whole. You might need to see how much of a strain a particular contact reason is putting on your Tier 2 and look into documentation to solve it, as well as informing the product team.
This is why being able to access your data in a flexible way - to play around with it and cross different dimensions of analysis to make decisions faster - is a huge plus. For example, you might need to cross data to the area where CSAT has dropped the most. In this current context, you don’t really want to constantly be building new dashboards to monitor non-recurring issues. Being able to manipulate your data quickly will save you hours of analysis in root cause analysis and in ongoing reporting efforts.
But it goes one step further too. A “click and play” solution like Miuros goes further in your data than your ticketing system or BI tool’s analytical capabilities. It computes new metrics from hidden data so that you can reveal unique insights: the kind of metrics take lots of pre-processing from data scientists to be fully leveraged through standard BI tools.
What’s also important, in the constantly-changing world today, is being privy to evolving situations. To make sure you’re on top of things, Miuros sends you notifications when your metrics drop below or go above your desired thresholds, so you can act as soon as something needs your attention.
Coherent data sets usable by multiple stakeholders
Miuros gives you full visibility over your support operations - right the way through to Quality Assurance - which allows you to respond quickly to changing pressures on your team; taking away much of the pain of managing those metrics alone in your helpdesk.
But what about all the other information your organisation gathers every day, that isn’t necessarily tied to customer service operations?
Every day, your customers generate product or service usage metrics (through trials, feature usage, purchases, session statistics and many more), they engage in your social channels, they talk to your sales team, they leave reviews on third party sites. With a raft of metrics and measures at your disposal, you can correlate almost anything to retention.
To do this effectively, you need to be able to tie metrics together from multiple systems that don’t automatically or obviously integrate.
This data and analysis can - and should - be made available to many teams: it needs to inspire conversations and processes that don’t ordinarily happen.
From a customer perspective, clients are demanding both excellently-executed and increasingly personalised experiences on digital platforms. This requires effective user identification across platforms and over time, and the ability to react quickly to changes in user behaviours across all teams in the business.
At Snowplow, we use all the usual tools our readers would be familiar with. We use Zendesk, OpsGenie, Jira, Salesforce and our own product usage data. We use Clockify to track time in the support team, too.
Pulling together all these data points to understand how we can best serve our customers’ needs might ordinarily be considered something of a nightmare. But the beauty of Snowplow itself as a platform is that it integrates with almost any system you can imagine, either natively or through webhooks. We can pull all this data together into our data warehouse and build the dashboards we need from there.
Even more than that, Snowplow doesn’t shoehorn the data into a format that only suits one team: it validates and enriches it so that it becomes a coherent data set usable by multiple stakeholders. Your support team and product team and success team and documentation team can all build views based on that single, enriched data set, that are meaningful to them.
Organisations often attempt to pull this together into daily, or weekly, or even quarterly summaries. It’s quite likely that this will be intensive, repetitive work for an analyst or leader in the organisation. But the Snowplow pipeline pulls all these data points together in real time.
Give yourself every chance to hear what your customers are saying
In a fast-moving, fast-changing post-Covid world, organisations need quick access to relevant data from support to be able to stay close to their customers and improve customer retention. They also need to be able to compile data from all other parts of their business. Whatever your role, you need it in an easily digestible format that can tell (complete) stories to your decision makers. Those stories change as rapidly as the world changes, and so you need to be prepared to respond to them as quickly.
In fact, in these times, we need to be more responsive than ever before to our customers' evolving needs; or they will take their business elsewhere.