Top 10 Customers by Revenue

A lot can be done with this list. For instance, we can send this off to the customer support team and they can proactively reach out to these ten people, offering them a gift voucher or free shipping for their next order and more. 

This represents “customer service goals”- so to speak –  accomplished in only a couple of minutes, thanks to operational analytics. Want a preview of how this can be achieved? Check out our free subscription below.

Setting up Operational Analytics for your Team

It’s easy to see the added value that operational analytics brings to any team or business, but in practice, it may not be received all that easily by your team. In fact your team may not actually use it if they’ve not been prepped. By nature, humans are resistant to change and having to learn how to work with a completely new tool is very much a major change. 

The best way to drive home the point is to not just talk about (several times) the value of the tool but to actually demonstrate it. If you’re able to, it could be useful to have a pilot testing group that works with the operational analytics tool that you choose to move forward with. Once they’ve been onboarded and know how to properly leverage the tool, you’d be able to show how much easier their day to day job becomes, with the help of that tool. Of course, it is definitely important to have some KPIs which track the goals and measure the performance of the tool here. Otherwise, it would be pretty tricky to show that the tool has made a difference at all.

Ultimately, we’re all simply looking to be able to do our jobs better, without the use of too many additional resources. 

On the other hand, a lot of times employees can be scared of automation and perceive it as something that will potentially replace their job role. It’s importance to note that operational analytics tools will simply address bottlenecks or enable people to do their jobs more efficiently and deliver on their tasks even more efficiently.

How Operational Analytics Helps Different Job Roles

We’ve talked about implementing operational analytics for your team and why it’s generally important. But it’s well worth it to understand how it can make a difference for different business roles.

Sales:

Which sales leader doesn’t want to hit better numbers? But with the usual methods of sales optimization, constructive criticism can be hard to come by. However, with operational analytics a slightly different approach can be adopted. For instance, instead of using a simple KPI dashboard, operational analytics can yield answers as to “how” individual sales reps reach their targets – e.g. how many calls or emails they need to send, or on average how the length of the sales cycle differs per rep. With operational analytics, sales leaders can spot why someone has a shorter sales cycle. 

Is it because of their style and frequency of follow ups, whether they are assigned a particularly lucrative sales region or whether they “hunt” more than their peers. Then, using this information, they can pass it on to those who need help or devise a better system of incentives. 

Marketing:

With marketing, operational analytics can be really useful – for instance, combined with a scoring system, operational analytics can tell you how a lead has been interacting with your web-pages. Using operational analytics, you can make highly customized recommendations to your customer – like if someone is based in Germany, your website can show them highly personalized suggestions based on locations. Or, if someone has visited your pricing page 3 times in the last few days, you can alert your sales rep and directly ask them to call the prospect instead of sending an email and trying to schedule time to talk.

C-Levels:

C-levels could find operational analytics particularly useful. While they’re strategizing about a new product or a new service, they can use operational analytics and metrics in real time to help define next steps and the direction in which they should proceed and more importantly, in which direction they should not. 

More importantly, rapid decision making and several iterations is a very possible scenario, with the help of these tools.

Additionally, the value operational analytics brings to Customer support and success profiles has already been illustrated earlier in this post. These are just some of the teams that can benefit greatly from operational analytics, but it’s definitely a pretty universally useful tool across teams and divisions in a company. “Digging deeper” takes on a whole new meaning, because with operational analytics, it isn’t synonymous with “waiting longer”.

Conclusion

Operational analytics essentially prevents your business and data teams from working in silos. Both sides can now refer to the same single source of truth when they’re trying to solve problems. And more importantly, operational analytics gives your teams the knowledge they need to take a call at exactly the right moment, as opposed to days later, after they’ve received their data report or gone through several rounds of back and forth with their data teams.

In today’s world of instant gratification, this is in fact a very useful value add for any sort of tool.