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Increasingly, companies need to merge data generated from multiple channels. But they are struggling with how to start with reliable data first.
Omnichannel customer service enables companies to interact with and serve customers seamlessly regardless of the channel they choose -- whether that's on a company's website, in email, by SMS text live chat or on social media. But data silos and operational hurdles have kept data and processes separate, which has stood in the way of solid omnichannel service.
Getting accurate data has been a particular sticking point, particularly where different departments have different conventions for entering data or other manual data practices come into play. A database may view company names with different capitalizations or abbreviations as completely different entities, for example, when they are in fact the same. An extra zero may be added erroneously when dealing with large numbers. Not to mention things as simple as forgetting to click Save. These touch points allow for faulty data to enter into the system, regardless of how careful we are when inputting the data. Needless to say, aggregating data from multiple departments or channels has been difficult.
Gleaning data insight
Good data practices don't end with data entry. Traditionally, once information was collected, companies would generate a report from the data to glean business insight. But this process was often manual, laborious and not self-service-oriented. First, departments would have to request the report from the data analytics department. Then business users would take the report, transfer data into a spreadsheet or charting software (like QlikView or Tableau) and cross-reference it with the department's own data. This process was time-consuming and still prone to human errors due to the amount of interaction necessary.
Today's new multichannel analytics
This traditional data analytics model was standard practice given the lack of processing power, network speed and storage space. But today, new tools can be synchronized across large databases and compared without the need to even export data. Dashboards can be generated for executives and managers in real time on laptops, tablets and mobile phones.
This kind of cross-business unit analytics can solve a persistent problem for business: visibility into the data. Honest, unbiased and empirical evidence of how operations, products, individuals are performing and, more important, how their performance affects other parts of business. Executives crave this level of multichannel analytics because it enables them to make decisions in real time based on evidence from the business. This power comes from how easily we're able to link points of data in different ways. Why build a graph in Excel every week when you can access the same data anytime you want on a dashboard? Why make a report that's obsolete in days when you can store the data and develop trends?
A simple productivity report shows units produced for the hours spent, for example. This kind of report provides a solid baseline for showcasing productivity. New tools allow us to go further. Let's take the same numbers and chart them per person and by hour. Now let's cross-reference those graphs with the ambient temperature and see whether temperature affects productivity. We can evaluate based on other variables, such as days of the week. You get the idea. This is what carefully planned and tailored analytics can offer a company.
This is also how companies want to stitch their data together: using as many options as possible. The potential of multichannel analytics comes from the data, but the power comes from the connections that are possible. This is one major reason why analytic platforms will need to continue to evolve their integration to allow these connections to occur.
One method for advancing communication in this area is the use of application programming interfaces (APIs). APIs allow secure access points for software to communicate through. Attaching an API to already formed data silos would allow analytic software to gain access to the necessary information.
In the future, the challenge is security and privacy. Because the greatest benefit to multichannel analytics is visibility, these two areas come with inherent risk of sharing sensitive data. Some customers might refuse service if they are being tracked. Concerning security, it's not just hackers. The competition is always looking for access to good data as well. Security protocols, best practices and clear EULA's should always be in place prior to initiating any new source for tracking data.
So although there is a risk associated with linking all of this data, the benefits are generally worth it: the ability to see into finances to reduce risk, the ability to measure efficiency to streamline operations, even the ability to analyze people to predict their future needs. The field of multichannel analytics has an exciting future.
Why multichannel customer experience is the mandate
Companies need channel integration for customer experience
Security considerations in a multichannel environment