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Analysis / eCommerce

The 3 Pillars Of Self-Service Analytics

Self-Service Analytics

Self-service analytics has the potential to deepen your understanding of your customers and redefine the way you interact with them. However, the key word there is ‘potential’.

Most tech professionals will be well aware of the myriad of benefits of self-service analytics platforms: the way they automate the process of manually building and updating databases to provide more flexibility, efficiency, and independence among a company’s various customer-facing teams. But that’s a sales pitch, not a roadmap for implementation – and many companies can struggle to turn it into reality. A recent report found that 85% of firms have launched programs to cultivate a data-driven culture, and only 37% have been successful.

Implementing any new technology is a considerable undertaking, and self-service analytics is no exception. While every business is unique and there can be no one-size-fits-all solutions, your company needs to make every effort to make a success of it. Here are the three pillars of self-service analytics:

1. User Needs

Self-service analytics cannot be adopted for its own sake. Like any other technological tool, it must advance your commercial and operational goals and meet the requirements of your various teams and departments. Full stakeholder buy-in is essential: the business’ managers and executives need to communicate the importance of becoming a data-driven company, and actively ask employees how they intend to use it and what they need from it.

Start small, with simpler analyses that can be understood using clear metrics. Over time, you can adjust the system to meet the specific requirements of your departments. It’s also worth investing in some user training at the very start: self-service analytics isn’t an area of focus for many employees, and getting them up to speed ought to be a priority. Those who understand it better than others can also play a vital role in mentoring anyone struggling with the technology.

2. Integration

No department is an island: they all contribute to the success of the business, and their efficiency and effectiveness are defined by how well they work together. Information sharing ought to be a priority – but data siloing is endemic for many businesses.

This is a problem. When data is isolated, it’s not working as hard as it could be. Worse, it can lead to internal confusion – which leads to a disunified, disjointed customer experience. Integrating analytical capability should be a priority. There is no reason whatsoever that sales, marketing, and customer service cannot share information: the process of generating leads, closing them, and ensuring that they’re satisfied post-sale is one that can clearly benefit from informational collaboration.

That’s fairly obvious, though. Other integrations can be just as beneficial, even if they’re not quite as intuitive. If sales shares information with finance, for example, both teams will have a better idea of whether or not new business efforts are resulting in higher profits.

And above all, collaborate with IT. The IT team is a reliable font of wisdom for any data-driven technology implementation: if you can take advantage of their expertise, when developing your best practices, do so.

3. Data Governance

Nothing ruins an implementation quite like ambiguity. You cannot foster interdepartmental collaboration if the rules are unclear and the data opaque.

A self-service analytics platform should be designed with maximum visibility in mind. To this end, businesses should ensure that they deploy a centralised data management system to facilitate easy access to information. The data held by this system should be regularly cleansed and updated. If this is done correctly, every department will work from the best possible information – hosted in managed in a secure, accessible way. Vigilance will be necessary to ensure the ongoing safety of this information.

Self-service analytics can undeniably be frustrating to implement. Keeping these three pillars firmly in mind will go some way towards making it easier, but it is still a process, and processes take time to get right. Take some consolation in the fact that, once complete, the benefits should prove themselves in short order. By gathering and using superior insights into customer behaviour, you’re not just understanding your target audience: you’re building a better business – one with foundations made of concrete, actionable information.

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Since co-founding sales-i, Paul Black has worked to develop a pioneering SaaS business proposition focusing on service architecture and delivery, setting the company’s technical direction and spearheading business and sales partnerships. Paul is responsible for the marketing proposition and technical delivery of the sales-i service. Paul was an early adopter of the SaaS model and during his 15-year career to date he has helped a number of businesses adopt and successfully deploy this software sales model. Paul was awarded his honours degree in International Marketing from Leicester University.

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