Developing a carefully considered omnichannel strategy is quickly becoming a priority for many business and local government organisations across the country. However, without a way of measuring its performance, there’s no way to know if it’s as effective as hoped – or even if it’s having an impact at all. Here we take a look at how analytics can help us ensure the omnichannel approach is working and explore a few key metrics that may be useful along the way.
How are analytics useful?
Analytics in an omnichannel context are useful in many different ways. Local governments can use a range of metrics to measure various phenomena, in the hope that they’ll help them achieve a number of aims. These aims often include;
- Mapping, evaluating and streamlining the user journey to ensure that users are seamlessly switching between channels.
- Monitoring interactions in real time, so that the system is responsive and able to provide up-to-date feedback.
- Improving collaboration between different parts of an organisation by providing them all with the same information and unifying them into a single omnichannel system.
However, analytics will not be able to achieve any of these aims if key metrics are not collated in an accessible and informative manner. One way of doing this is through the use of Operational and Managerial Reports. These reports bring together in-depth data on a variety of subjects, allowing those running an omnichannel strategy to assess their progress.
There are an incredible number of metrics emerging to help measure the success of an omnichannel strategy, many of which will soon replace those we’ve regularly used in the past. Below, we take a look at five of the most important metrics for organisations looking to measure the efficiency of their omnichannel approach.
First contact resolution
First contact resolution is an important metric for measuring customer satisfaction and mapping the user journey. In the past, many organisations have chosen to measure first call resolution, ignoring the fact that users may have already spent a considerable amount of time trying to solve their problem elsewhere. In the context of local government, a user may have accessed resources on the website, watched a video on a YouTube channel, or interacted with a chatbot before using the phone.
ICMI research indicates that 82% of consumers say the main factor in a great customer service experience is the quick resolution of their problem. If users are having to access numerous different channels before picking up the phone, their problem is not being solved quickly and organisations are ignoring a large portion of the user journey.
Customer Effort Score (CES)
CES measures the ease of the customer experience in dealing with an organisation. In some circles, it’s thought of as a more accurate way of measuring customer loyalty than similar Customer Satisfaction Scores (CSAT). This is down to the relatively new idea that organisations do not encourage repeated use of a service by ‘wow-ing” the user but by making the service as efficient and easy to use as possible.
A CES can be generated in a number of different ways, though one of the most popular methods is a simple feedback question along the lines of, ‘overall, how easy was it to solve your problem today?’ It’s particularly useful in local government contexts due to the way it measures the success of the customer service experience – a particular area of focus for local government – and can offer indications as to how seamlessly users are moving between channels.
Final sale attribution
Final sale attribution is an interesting metric that’s included in this list due to the way it’s often used without thought for omnichannel strategy. Final sale attribution measures where a sale was finalised and completed. In the context of local government, it could be used to measure where a problem was finally resolved. Superficially, this seems an efficient way of comparing channels and measuring the success of each.
However, final sale attribution fails to account for the user journey beforehand and often over-emphasises the importance of the channel in which the point of sale is made. For instance, a customer could browse through a catalogue, find a product they like and contact customer service to find out whether it’s in stock. The customer service rep advises the individual that it’s not in stock at their local store, but another nearby store does have stock. The customer purchases the item at that store instead. Final sale attribution would identify that store as the point of sale and consequently emphasise its importance, even though the nudges towards the sale by the catalogue and customer service rep were of equal importance. While final sale attribution is sometimes a useful metric, it needs to be refined and improved if it’s to remain relevant to omnichannel analytics.
Social media shares
Social media provides enormous amounts of analytical data that’s of great use to businesses and local government alike, and that can be put to good use in omnichannel analysis. Metrics such as ‘likes,’ ‘shares,’ ‘retweets,’ and ‘click-throughs’ can tell us a lot. Not only do they provide useful data on user demographics for each channel, they also allow organisations to target channels at specific user groups.
For instance, recent research has demonstrated that, compared to the general public, a higher percentage of university students use Facebook. This means that local governments looking to target their services may want to consider a Facebook chatbot (or similar technology) to improve communication with this particular demographic. Using data to target specific groups through the most efficient channels is absolutely essential to an omnichannel approach.
The view-through rate
The view-through rate measures the number of users who, having interacted with a particular channel, go on to perform an important interaction in another channel. This gives you a clearer idea of the early stages of a user journey and moves away from an emphasis on final sale attribution. It can also be useful in justifying investment in those channels that aren’t traditionally perceived as a good return on investment, encouraging a more comprehensive omnichannel approach in the process.
When a new conceptual approach emerges to challenge the business models of the past, it tends to require new ways of measuring its performance and judging its success. This is what is currently happening with omnichannel analytics. While the five metrics listed above are important means of measuring progress, they may be replaced with more accurate measurements as businesses adapt and get to grips with the omnichannel approach. Omnichannel strategies are not static and should change to reflect technological and market developments. As this happens, organisations also need to be prepare to alter their metrics and change the way they measure success.
Have a question or want further information on omnichannel analytics? Our expert team have been providing customer contact solutions for over 25 years. Call us on 01344 706111 or drop us a line.