|By Michael Bosonnet, strategic planning and data analytics consultant|
In the 18th century, Josiah Wedgwood made a promise to customers; “satisfaction, or your money back”. He is credited with pioneering many of the tactics used in marketing today.
With new marketing metrics including NPS and customer retention rates coming to the fore there is increasing focus not only on revenue growth but also on customer satisfaction and customer lifetime value as measures of success.
According to Salesforce, 60% of marketers now track customer satisfaction (CSAT). The MIT Sloan review, a study that analysed stock performance versus CSAT, showed that satisfied customers generally do not result in financial performance in the short term. The key to ensuring a better link with CSAT and business performance is achieved by managing the resources invested in driving satisfaction over time. An article from Harvard Business Review echoes this sentiment that non-financial metrics, such as CSAT should be measured on a case by case basis with the bottom line in focus.
However; satisfaction and financial performance are not inextricably linked. The low cost airline model comes to mind when thinking about businesses that have accelerated their ability to make a profit and may not necessarily have high CSAT scores. How do they achieve this? By cutting every single overhead down to the absolute essentials and looking at what is called ancillary income.
At a recent Travel Massive event in Dublin, members from the airline industry discussed the importance of selling other services beside a plane ticket. This income helps a business to maximise profits and often it does not increase operating costs, for example charging money to board the plane first or bring cabin luggage, costs the airlines very little and can make a big difference to the financial statements.
How can other data points improve the chances that satisfaction will result in increased business performance?
According to Harvard Business Review, CSAT can be measured by identifying the metrics that correlate with an increase or decrease in satisfaction. For example; on a customer success team, a key metric driving or reducing satisfaction scores could be the amount of time a customer has to wait for their ticket to be resolved. Often, at the end of a call with a service provider a client will be asked to participate in a short survey. This survey contributes to the CSAT and oftentimes the NPS (Net Promoter Score) for a business.
Does this data analytics approach to satisfaction result in increased performance? A key learning from industry practice is the importance of managing the resources that the business invests in maintaining satisfaction scores, while also managing and maintaining satisfaction levels within teams.
At present there is both a surge and enhanced convenience in available data from which to garner insight and ultimately make decisions. Salesforce research showed an increase of 50% in the number of data sources that customers are using to power their decision making. Companies in operation have access to both manageable data streams and big data. Big data sources are becoming increasingly valuable, because they allow companies to mine large data sets to feed into internal departments. Big data usually takes the form of a database and requires a programming language to analyse and decipher.
If you’re wondering about big data, Gartner is considered the most widely used and understood definition. Big data is the volume, variety and velocity of information available that is simply too large for traditional methods to analyse. Companies in operation today use data analysts to run queries, extract information and help form the basis of decision making. One of these metrics could be a satisfaction score joined to a customer Id.
There is a growing expectation for marketing departments to become more data driven. According to Hubspot, 80% of CEOs do not trust their marketing departments, based on a global CEO study. Marketing is generally seen as responsible for building a relationship with the customer and therefore have CSAT, value and retention built into their mission. Data can certainly help to inform decisions, for example big data insights can be fed into team reports. This could mean that a marketing team looks at a dashboard for weekly insights about their customers and observe CSAT scores, but is this enough? How can businesses truly know that satisfied customers are resulting in a return on investment. Is it as simple as building a relationship and managing the available satisfaction data points or is it something more?
This is where Customer Lifetime Value or CLV comes into play. CLV measures the value a customer is likely to bring during the entire relationship with the company. It is well-known that it is more cost effective to retain existing customers than to attract new ones. In an article from Google, it is now possible to use artificial intelligence and machine learning on the cloud to predict CLV. This is done through training models to understand what they call the recency, frequency and monetary value of a customer.
It is also important to understand context. A customer that makes one large order may be worth less than a customer who purchases smaller items more frequently. This makes sense when you consider some of the tactics used today in retail, for example encouraging the customer to add one extra item to their basket. Qualtrics highlights the value of the CLV metric in building the customer experience programme for a business.
For any marketing team, what they should be asking themselves is simply, “how can we keep our customers satisfied and motivate them to return”.
In today’s world, customer sentiment is measured with a number of key metrics including, customer satisfaction (CSAT) and customer lifetime value (CLV). The latter is growing increasingly popular in the age of data analytics and Google has recently launched a new CLV metric into Google Analytics, currently in beta mode.
Customers are essential for any business. Without customers, a business cannot continue to run. An essential mantra for any business in Ireland and abroad today is “Know Your Customer”, coined by the retail expert Mary Portas. In the world we work in today, it is as important to manage the customer metrics that guide decision making, as it is to have a relationship with customers, through marketing or at the coalface.
Michael Bosonnet is an expert in designing and conducting primary and secondary research activities, including surveys, focus groups, stakeholder consultation, desk research and new methods, such as social media sentiment analysis.
He has spoken about the application of data analytics and RADAR to projects in HubSpot Dublin, Culture Night and Creative Mornings Dublin. He also lectures in data analytics, and real-world research methods.
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