3 Rules for Implementing Self-Service Analytics
In 2017, jobs that don’t require a high level of technical literacy can still make excellent use of technology. The power of Business Intelligence (BI), for example, can be harnessed by people without expertise in data science and statistical analysis – so why should it be reserved for specialists?
A growing trend in BI, ‘self-service’ analytics is designed to make big data insights available to anyone who needs them to meet their strategic goals. It’s a growing priority for many sales and marketing teams, who value the independence, flexibility, and efficiency it offers. When you don’t have to do much legwork in terms of building and maintaining databases, conducting analysis, and creating reports, you inevitably have more time for other considerations.
But adopting self-service analytics isn’t necessarily a straightforward process. Like adopting any new technology, it’s a process that requires strategic planning and research, implementation of new policies, and effective collaboration to be a success. Accordingly, if you’re part of a data-driven sales and marketing department, you’ll want to keep these three rules for smooth implementation firmly in mind.
Align technology with needs
Before you adopt any new technology, you should make sure that it complements the needs and capabilities of your department and the wider business. This is an action that should be driven by those at the top of your business – senior managers and board-level executives. Becoming a data-driven organisation requires full leadership buy-in.
Any software you roll out across the business will need to be intuitive, accessible, and convenient for all end-users, so ask them what they want to see from this technology. Start small and analyse performance according to clear, easily understood metrics. However, be prepared for change: needs, capabilities, and expectations will adjust over time, and it’s vital that your company is willing to adjust with them. Use routine training sessions to get colleagues up to speed, and identify ‘super users’ to mentor any who might be struggling.
And, if your rollout is a success, think about how it could impact other departments. If you can encourage HR, finance, and other strategically important teams to get on board with this technology, then you’ll all benefit from greater shared analytical capability.
Create a company-wide data governance policy
When using shared analytics platform, it’s imperative to take steps to avoid data siloes. When information is isolated in disparate systems, it limits your transparency and your ability to collaborate across teams. The left hand won’t know what the right hand is doing – limiting operational efficiency and preventing you from doing your best work.
All self-service tools should be managed with maximum visibility in mind. They must be integrated within a unified and centralised data management system, offering all users access to a single source of unquestionable truth. Introduce rules for data cleansing practices to guarantee that data is up to date and relevant. When you’ve created a data governance policy that all departments can adhere to, you’ll also reduce your risk of data breaches and loss.
Encourage interdepartmental collaboration
Sales and marketing departments would do well to deepen their relationship with the IT team. With data-driven technology growing in importance, this is already becoming the norm: everyone is responsible for using information to improve the customer experience. Self-service analytics encourages you to harness more information for sales and marketing purposes, but the IT team will do much to guarantee a smooth implementation period – creating best practice information, assisting with security challenges, and serving as the first port of call for any technical questions.
This doesn’t mean that they’re there to hold your hand through the process – but it does mean they shouldn’t be totally hands-off. Strike a balance, and aim to foster an environment where everyone can work comfortably with self-service analytics and the new capabilities it supports.
Every modern sales and marketing team should become more comfortable with using data to inform their actions. It makes you more agile and proactive, more independent, and it empowers you to make better decisions. When you’ve developed your self-service capability, you’ll benefit from superior insight into your prospects, your customers, and your strategies.
If, for example, an end-user’s purchase history harbours hints as to their future behaviour, you’ll know about it, and be empowered to take pre-emptive action before they defect to a competitor. If they express a preference for being contacted at certain times, or on certain formats, you can be aware of it, ensuring that you don’t irritate or alienate them. If they often buy several products and services discretely, self-service technology can immediately alert you to their favoured combinations, giving you the chance to devise bespoke offers.
Best of all, this barely scratches the surface of what data can do. Knowing what your customers want and how to give it to them is the holy grail of modern sales. Self-service analytics can help you do just that – if you take care and follow the above three rules before, during, and after the implementation period.