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How to use all your data to build true business intelligence

Posted by Perceptive Team - 10 March, 2021

What is business intelligence?

Intelligence is the ability to acquire and apply knowledge. Business intelligence follows this same definition but in a commercial context. And while acquiring knowledge and putting it to use is simple in theory, the reality is much more challenging. True business intelligence requires a combination of several data sources, expertise, tools and software to sort, interpret and analyse this information to turn it into knowledge that is both meaningful and actionable.

PR-BI020 C17 Paymark Blog ImagesC17-Build-true-business-intelligence-830x405Business intelligence versus business analytics: what’s the difference?

Business intelligence is closely related to business analytics and we often see the two used interchangeably. At Perceptive, we consider business analytics as a part of the larger intelligence whole. To use business analytics is a means to acquiring knowledge, its experts and systems aggregate data, analyse it and turn it into information. Business intelligence is applying that information into a business.

In short, business analytics is the beating heart that powers the business intelligence brain, you can’t have true intelligence without it.

But before you get business analytics or intelligence, you need data. And true business intelligence needs a variety of data sources to draw on—from big picture mechanics to one-on-one customer experiences. As a rule, the richer your data sources, the better understanding you gain.


The 5 altitudes of data for true business intelligence

“Business intelligence is like a jigsaw, when you have all the pieces of the puzzle you get a complete picture of your market, your business and your customers and how they fit together,” says Oliver Allen, General Manager at Perceptive.

Which is why it’s rarely a good idea to follow guidance from one piece of the puzzle, i.e. one data set. If an insight isn’t corroborated across multiple data sets, it could easily be a red herring, which could have ramifications on your business.

“You need diverse data to know that the conclusions you’re drawing from it are correct. With diverse data you have a greater sense of surety,” says Oliver.

So what types of data should businesses be gathering? We’ve broken it down into five distinct altitudes or levels of data.


1. Macro trend data

A big picture overview of the industry you operate in be it B2B, B2C, NFP, Government and so on. Data at this level helps you explore all the macro trends that are influencing consumers now and into the future. With it, you can analyse market size, market segmentation, social and cultural trends, and product/service feasibility to predict where the market is moving.


2. Market data

This altitude is about understanding how consumers in your market think and behave. Data at this level is a mix of attitudinal and behavioural, which work in tandem to reveal the relationship between what consumers say and what they actually do. Tools such as transactional data analysis, econometric modelling, human behaviour analysis and testing, and new product testing all help explore this level, as do methodologies such as customer journey mapping and pricing strategy research.


Read more: The power of claimed versus actual behaviour


3. Brand data

Data and business intelligence at this level is all about understanding the role your brand plays in consumers’ lives. From brand awareness, what drives your customers to choose your products and services over others, and the brand attributes that brings customers to your door. Methodologies such as brand tracking and brand strategy are critical at this level. With them you can build out your understanding of customer needs, identify opportunities, set strategies and measure growth.


4. Customer data

This level is about using your customer data to deliver greater value to your consumer. It draws on the data your customers generate with your brand, such as marketing engagement, spend, tenure, frequency of visits. Services such as a customer value management programme can help you pull all this customer data together to help you deliver powerful and engaging brand messaging, create customer-centric products and services, and build great brand experiences.


Learn more: Meet Ada, our fully-visualised, self-service dashboard that aggregates EFTPOS transactional data from across New Zealand.


5. Experience data

From your customers to your employees, the one-to-one experiences they have with your business can be captured, measured and used to build deep, personal connections to your brand. Data at this level is collected from tools such Voice of Customer surveys and analysed in customer experience and employee engagement programmes. With this information in hand, you can uncover ways to improve customer and employee experiences at specific touchpoints, enhance your products and services, and drive immediate improvements and operational changes in your business.


Having diverse data is not enough

While gathering, sorting, interpreting and analysing diverse data sets is a step in the right direction, it will mean nothing without a data-driven culture in your workplace. In short, your business must be open to evidence-based decision making. You must be prepared to create dedicated, specialised resources to manage your data analytics to reap its benefits, from hiring the right people (be it in-house, a consultant or via an agency) to investing in business intelligence tools, programmes and infrastructure to get the most out of your data.

True business intelligence is having diverse data across all altitudes—and a mindset to match.


Want to start building true business intelligence? Learn how transactional data can level-up your customer understanding in our free transactional data guide!

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Topics: Customer Insights

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