Analytics_Transforming_CustomersIn the data-driven age we live in, the use of analytics is extremely important to marketers. Without them, data-driven insights are extremely hard to come by.

Driving core business KPIs using analytics is something that most successful marketers use in their approach, but even the marketers with non-analytics backgrounds are starting to build up their analytic knowledge to be more effective. There are now many analytic platforms and tools available that non-technical marketing teams can use to extract powerful insights from their data.

Below are a few tips on how to help marketers integrate data and analytics into their marketing strategy.

Using Customised Dashboards

Post-event reporting is something that most analytical tools allow you to do, but the demand for more real-time relevance from customers has brought around a change, and now the tools also allow for marketers to access highly customisable and real-time reporting based on marketing metrics that matter the most to their business.

A big step towards marketing success is tracking the right metrics, and marketers can now do this a lot easier by building dashboards based on specific use cases that allows the users to identify not-so-obvious patterns, rather than tracking a variety of metrics like traditional dashboards.

Finding the Dashboard Target

With the option to track so many different metrics and dimensions, your dashboard can become a very cluttered and complicated place if not careful.

Rather than getting stuck in a load of analysis and becoming bogged down, make sure to define the use cases that matter the most to your business so just they can be measured.

Mindful Towards Your Data

Data is claimed to be the core element of marketing campaigns by many marketers, but without a centralised data repository, there’s a big gap in knowledge and execution. With so much data at their disposal it is becoming a difficult challenge for marketers to inspect customer and product data across a multitude of consumer interactions and touch points.

Your analytics can only be as good as the data it feeds on, as the foundation of strong insight-driven analytics rests on the quality of data and a complete view of the customer journey. If the data is unstructured and of bad-quality, it can seriously end up affecting your analytics.

Choosing the Right Visualisation

The presentation of your data is extremely important, as data is only as valuable as the insights that it projects. Huge volumes of data can be hard to interpret, but when presented well, data can be acted on upon quickly.

Picking the right type of chart for each use case is where the magic lies for delivering actionable information from your data. Randy Olsen, AI researcher and data scientist commented on OlCupid’s use of visualisations, “OkCupid wouldn’t be nearly as widely known if its founders didn’t take a step back and think about how they could use data visualization to communicate the compelling stories in their data. Most companies have interesting stories to tell with their data (or others’ data), yet those stories won’t capture people’s attention with walls of text to read through.”

Making Use of Advanced Analytics Tools that Measure and Predict

Most modern analytical tools available in this era of real-time and predictive marketing embed machine learning and artificial intelligence to be able to predict and prescribe to users.

With this ability, it can be used with customer segments to accurately predict and prescribe which are the most profitable, and what kind of personalised promotion will work best for a customer or segment – in turn boosting revenue.

Marketing is no longer gut driven. Being able to analysis your campaigns in real-time is the ultimate way to extract valuable data and optimise. Retail analysis is now about enhancing the whole customer journey rather than just the next sale.

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