Knowing and understanding customers and their behaviour is at the centre of every successful business.
Customer analytics are an essential part of any organisation’s marketing mix. While it is widely accepted that using a metric-based approach to managing a customer relations strategy is critical to a business’ success, there are often misunderstandings between business users and data scientists in exactly what can be achieved as part of a customer analytics project.
Business users are the owners of what they would like to know about their customers and data scientists are the experts at crunching data and applying supervised and unsupervised statistical modelling on a titanic amount of data.
The gap always exists in terms of the business users understanding what can and cannot be achieved and in what amount of time and data scientists capabilities in understanding the business requirements, mapping that in technical terms and managing different pieces of technical implementation efficiently to deliver the desired and expected insights back to the business users.
An effective customer analytics project manages different pieces of technical implementation efficiently to deliver the desired and expected insights back to the business users. Yet 80 per cent of customer analytics project failures is a result of poorly defined, conflicting, misinterpreted or missing requirements, or even something as simple as not being able to action the insights in business processes.
A Key Bridge
Business analysts are the key bridge between the different working teams. They understand the business case for the insight and analytics programme and map that down to day-to-day activities with the business processes. They then collaborate with individual business users to gather and understand their requirements.
A key part of their job is to categorise and prioritise the requirements and then communicate them to a variety of stakeholders and manage their changes throughout the project lifecycle. Often business users do not know what they want and how to use the insights when they get them. A business analyst understands the technology and data aspects of the requirements and with the support of the tech/data science team represents its possibilities and constraints to business stakeholders.
A business analyst understands the technology and data aspects of the requirements and with the support of the tech/data science team represents its possibilities and constraints to business stakeholders.
A Continuous Conversation
A continuous conversation with the business users with respect to business requirements changes, early feedback from prototypes and sprint demos and carrying out the UAT and user trainings helps the users to know what’s coming and how they can use it to their advantage.
Most importantly a business analyst manages all this in a very agile and adaptable manner, so all the stakeholders have a good view of the progress in terms of the functional deliverables and outcomes from the business case
Business analysis for customer analytics is a key cementing material with a broad range of capabilities, tool skills, industry knowledge and above all the understanding and diplomacy in technology, data and business relationships. Customer Analytics is not a tech solution or a data problem: it is a business-led capability.
To find out more about how Acrotrend can help you with your Customer Analytics take a look at our “Customer Analytics as a Service Solution“