Whether you are creating surveys or if you have a database of all customer communications, being able to use this information to make better decisions at all levels of the company is necessary to improve overall performance.
We are in a situation where we have the capabilities to constantly see what people think about our companies and then base decisions around them. Using social media or even web based feedback forms, we can see every aspect of people’s opinions of our brand and products.
Collecting the information can be difficult, but with new big data technologies, it is possible to collect, analyze and display this information better than ever before.
The question is, what should companies be doing to make the most of this?
We believe that there are four key elements that companies should be looking at:
Personalized For The User
The data that can be collected about an consumer is vast, from their purchase history through to their communications directly with representatives. Data can even be several levels above the individual too, focussing on the thoughts of demographics or geographies to make the most of the brand in those areas.
However, different departments and different management levels require vastly different data to fulfil their roles effectively. Senior management need to see a holistic view in order to steer the company in the right direction, whilst those dealing directly with customers will need to see what is needed at an individual level to make sure that the person they are dealing with has the best possible experience.
Having personalized views of the data where everybody in the company can take full advantage of the data they need will be key to making sure that the data is used effectively.
Make It Actionable
Data can only be as good as the actions that it allows, which then need to be assessed and acted upon again.
The data needs to point towards a certain behaviour or action for either an individual or the company performance as a whole. Having the ability to assess how this change has affected performance is key to ongoing success with data.
Simply having data on what has happened is only as good as the impetus to use this for change and this change is only as good as the data says it is.
There is always more customer data to collect that can help to improve your performance, from the most basic such as surveys to the complex, such as analyzing every mention of your company on social media.
It means that there is always a new way to collect information and the companies who take the time to investigate the best ways to do this are going to be the ones who see the most useful data being produced as a result.
Using sentiment analysis through social media can mean that the general consensus of the company is evaluated as a whole, but the process requires considerable analytical effort and data storage capabilities. This is because not every tweet or Facebook post will be relevant to your company. For instance, around 3 years ago our company name at the time was used in a series of tweets by somebody from 1 Direction which then had tens of thousands of retweets and responses. A basic system would not have picked up that this was not related to our company and instead analyzed the sentiment incorrectly.
It also requires a certain understanding of sarcasm, something that is still not a perfect science. It means that analysis could show a negative meaning but in reality be positive or visa versa, further skewing the results.
In order to process data, it needs to exist in the first place.
This may seem basic, but in order to do this there needs to be constant opportunities for customers to do so. If you can do this within an environment that you control then it works even better.
This could be either through fields in web forms, collections of emails or even a basic survey to establish behaviour and thoughts about the brand. Through regularly giving customers the opportunity to give their feedback in the way that works best for them you are going to have the best results for your data gathering programme.