How KNOWN Data Can Improve Your Customer Experience
Digital transformation has led to a new era of data gathering, all thanks to digital tools that allow for the tracking of information on a scale never seen before. Whether you are interested in gathering information on how users interact with your website, or if your couriers are optimising their travel routes on a national level, or if your contact agents across your entire global organisation are not dedicating enough time to their customers, you are able to gather and stockpile this kind of information. These stockpiles of data have been classified as big data.
Unfortunately, just having access to big data isn’t a benefit on its own. Many companies invest heavily in these data gathering systems so they can make use of it, and then have no idea what information they actually have, or even how to use it.
To use another metaphor: if businesses were trying to bake a cake, they would have the key ingredients and utensils to make one, but they wouldn’t know how to use them to actually create the cake. Companies don’t know how to take the data they have, and use it to create KNOWN data that results in actionable intelligence.
Why?
Why is this KNOWN data important to companies and customer experience?
Firstly, KNOWN data will help you understand your customers better. For example, KNOWN data can provide you with answers on how and when customers interact with your organisation via social media, or how changes in your country’s government are negatively affecting customer spending. You can then take steps to improve customer interactions, or soothe your customers fears so that they return to their usual spending habits.
KNOWN data will also help you improve your ROI by specifically creating actionable intelligence, such as helping you identify inefficiencies in your employees workflows or in your automated systems which you can then rectify. This is in contrast to data that you can’t use to create any changes in your organisation.
How?
Even if your organisation is financially sound, it might only function on a basic level. You need to take advantage of the KNOWN data you have to optimise your company. This can be achieved in several ways.
The first step is to bring in expert analysts who can help you sort and identify the KNOWN data that will be useful to your organisation. Analysts will be able to assist you by identifying trends using the data you’ve gathered.
For example, if your contact center is required to serve multilingual clients, you may have data that helps identify when you need different employees to deal with different customers.
After all, there’s no point in having 80% of your English speaking staff on shift if only 30% of the customers calling in speak English during that period.
Analysts will also be able to identify other operational inefficiencies using this KNOWN data and help you break them down and resolve them. For example, if some of your contact center staff have punctuality issues, but have to switch between multiple modes of public transport during peak hours, you may be able to resolve this by changing the shifts they work. Experienced analysts will also be able to help you use KNOWN data to identify and quantify your opportunity costs, not just actual measurable costs associated with running your organisation, and provide their clients with a consistent flow of information, based on the KNOWN data they have gathered.
Secondly, you need to ensure you have the right data assessment tools to identify and make use of the KNOWN data, and that you understand how to use these tools properly. Some organisations offer bespoke data assessment tools that can easily integrate with multiple APIs, simplifying the data analysis process.
Finally, you will also need to integrate functional support areas, and, depending on your industry, ensure you have the right analytics tools. For example, your contact center will need to ensure they utilise tools that suit their specific needs. Organisations don’t need to purchase analytics tools to deliver at the basic and co-ordinated levels. With this being said, ensure that your data analytics takes the various support functions, including Management Information, Workforce Management, Quality Assurance, Customer Experience, Business Improvement and Business Intelligence, into consideration so that you provide an integrated view to business at an enterprise level.
Merchants is an organisation that wants to help you optimise the efficiency of your business using KNOWN data. Here is one case where Merchants was able to assist a bank who had invested in cutting edge data gathering tools, but were unsure how to use the tools properly and leverage the information they had gathered. Merchants was able to take this data and present it in such a way that this KNOWN data was not only actionable, the bank was surprised they even had access to that kind of information.