Improving productivity often starts with improving contact rates, but putting as much emphasis on the managing your data can be equally as beneficial.
Improving productivity in contact centres often starts with looking for ways to increase contact rates, which a good predictive dialler will support you to achieve.
However, there are additional steps you can take that will improve agent productivity and the performance of your campaigns even more, such as keeping a close watch on how your data is performing.
Keeping a close watch on your datasets not only allows you to improve customer contact and data penetration, it also helps you manage resources within your operation more efficiently, improving customer relationships and helping you stay on the right side of industry regulations.
The deeper you can delve into your data and track the performance of it through multiple different levels, the richer the information you can gain and turn into actionable insights. Being able to analyse performance at a data source level is great, but the data from each of your sources is likely to be made up of various data files. Through the ability to analyse each of these data files, it not only allows you to compare data providers against each other, but also allows you to compare the individual data files you’re getting from your suppliers against one and other.
It’s a waste of time and effort to continue ploughing resources into data that is not accumulating the results you had hoped it would, because your resources – your agents – are time that could be better spent focusing on other data and money in wages. Through analysing data performance, on both the wider data source level as well as the more focused individual data file level, you can identify better performing datasets to focus your resources more heavily on – whilst identifying those to retire.
Similarly to above, the ability to monitor the performance of data in real-time ensures you needn’t delay the task of optimising your data. Analyse data against multiple statistics of your choice, allowing you to take decisive action through the insights you gain. Identifying weaknesses sooner rather than later enables you to quickly realign your data optimisation strategy, meaning any datasets clearly wasting your time and resources can quickly be nipped in the bud and pave the way for higher quality data leads to become the focus of your efforts.
Having the ability to route calls from within a particular dataset to your own chosen priority teams is a useful tool. It will instruct the dialler to attempt to allocate calls from any of your chosen data sources, and even individual data files, to an unlimited selection of teams. This is particularly beneficial if you know you have teams that will perform better tacking certain groups of data than other teams, giving you a clear incentive to keep on top of the organisation of your teams. Aside from increasing your chances of success by allocating calls to “better” performing teams, it also improves customer satisfaction as customers are more likely to be connected to the most suitable agents based on the nature of the call.
Inaccurate, out of date and duplicated records are just some of the problems that regularly cleansing your data can solve. Aside from poor quality data being detrimental to the success of your campaigns, failing on these fronts also poses other risks to your contact centre. For starters, dialling individuals that have specifically asked to not be contacted not only reflects negatively on the image of your business, it is both bad for the customer experience and even, more seriously, likely to result in you landing in hot water with industry regulators. Regularly scrubbing your data of records registered on the TPS, for example, can safeguard your business against potentially large fines and ensure the numbers you dial are perfectly compliant.
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