We’ve all heard the story. The “average joe,” who’s worked a regular job and lived a pretty contented life, happens upon the right combination of numbers and strikes it rich with a winning lottery ticket. His or her seemingly simple but happy life goes into overdrive and suddenly the world is their oyster. Sports cars, boats, new homes, electronics, designer wardrobes – even sharing money with friends and family – it’s all there for the taking. And it’s easy – for those who aren’t disciplined – to go and blow the money, a little at a time, until they’ve gone through the winnings. The lottery should be the answer to all their problems, but for many, the money creates more complications than it brings solutions. Sure, they’ve got “things” to show for their winnings, but a lack of planning means they have no way of supporting themselves (or the upkeep required of these new possessions) over the long term. They didn’t govern themselves and missed the opportunity that the money afforded them – to create a self-sustaining model that would have allowed for long-term stability and a luxurious lifestyle that could be perpetually maintained.
Data Jackpot
In some ways, interaction analytics can be a bit like winning the lottery. You’ve followed the advice from our previous posts in this series, carefully selected a vendor and have implemented the solution. Now it’s time to operationalize and you’ve unlocked this wealth of intelligence that was previously trapped in your contact center interactions. Suddenly, you have a new way of understanding the experience your customers have when they reach out to your company via phone, email, or chat. Many companies aren’t entirely sure what to do with this information, or the best way to utilize it. Just like the lottery winner, they lack governance. This can lead to two things.
Observations, but Not Pieces that Solve the Long-term Puzzle
The first is something I like to call “tidbit analysis.” This is like spending your winnings by buying a lot of small ticket items. In essence, tidbit analysis occurs when an organization identifies lots of “one off” scenarios, without thinking about how they factor into corporate goals. Interaction analytics can “find” anything, but is it valuable? For example, interaction analytics may be used to identifywhy a certain call type has increased in volume this week or identify random observations about your competitors. The problem with tidbit analysis is that you end up with a lot of short-term observations that don’t address long-term goals. Now don’t get me wrong, there’s a lot of valuable information that’s uncovered in tidbit analysis. It unearths business processes and agent behaviors that are affecting the customer experience and address very real needs of the company. However, it’s often focused on problems that only resonate in the contact center and won’t lead to the type of transformational data that brings movement to corporate metrics.
Too Many Choices
The second thing that happens without governance is what we’ve all heard referred to as analysis paralysis. Again, like the lottery winner who can now fill their closet with so many new clothes that getting dressed in the morning becomes an almost impossible task, an investor in interaction analytics can easily become overwhelmed with all the calls there are to investigate and all the use cases for the technology. The temptation will be to spend a little bit of time on each topic, without thinking about how they work together towards a greater goal. The problem is that you end up with a lot of fragmented information, and no real way to piece it together into a meaningful action plan. It’s not uncommon for 3 out of 4 requests for information using interaction analytics to go unused because too many requests are made, and the requests are too unfocused. The end result is so much information that it becomes overwhelming, with no clear direction as to where to start to implement change, so none happens.
Best Practices
So how do you go from the lottery winner who blows his winnings in the first year to the one who is able to live off them for the rest of his/her life? It’s all about following a few best practices and applying a little bit of discipline.
- The first best practice is to start with a business objective/question. It’s important that the business case align to strategic, corporate objectives and is something that the company is prepared to take action on based on the findings. Interaction analytics shouldn’t be used as merely a tool for targeted listening, or a way to identify example calls based on specific criteria. It should be the solution that allows companies to create hypotheses, identify metrics, extract data to measure against the metrics and then quantify business issues to develop prescriptive recommendations that solve for the original hypotheses.
- The second best practice is to ask specific questions and expect quantified answers. The right interaction analytics tool will go beyond the narrative and will provide empirical data to quantify the results. While context is important, in order to make business changing decisions, you need to understand the true impact an issue is having on your customers’ experience so you can measure the effectiveness of your change.
- The final best practice is to make that change, regardless of size, and spend the effort to measure the results. For interaction analytics to be self-sustaining, it needs to continuously deliver a return on investment. This simply isn’t possible if none of the findings are ever implemented. This needs to be thought about before the business issue to be investigated is even chosen. If it is one that is too tricky to change politically, or is not as “important” to your boss,, then it shouldn’t be prioritized (at least initially)as an interaction analytics project. Furthermore, once an action plan is created and takes effect, the results need to be continuously monitored so that adjustments can be made and the outcome is articulated in hard numbers.
Final Thoughts
Just like a lottery winner will benefit greatly from a financial planner who will help them invest their money and create a structure so they can live off the benefits of free money for generations to come, a company who invests in interaction analytics needs a strong services partner. Those who have a managed business and analytic services team who can guide you to use the solution as a driver of enterprise change will see significantly higher returns on investment in a much shorter timeframe. Having a partner who sets the governance framework to ensure that you’re on a strategic path, rather than an ad-hoc one, will make interaction analytics part of your company’s DNA, and thus an integral part of bringing about transformational change.
For more best practices around governance to help you maximize your interaction analytics investment, watch our slideshare.
