How to use customer data insights for more effective marketing strategy

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The crucial evolution in marketing and advertising, in general, is the ability to understand what kind of data you have, how to organise it and how to activate it.

A decade ago, many marketing experts were right when they predicted that data would become an integral part of any marketing strategy. More than 70% of marketers are confident in their data-driven approach and expect to increase their marketing budget in the upcoming years, focusing on targeted messaging, AI and tailored product development.

However, structuring and managing data is a challenge. On average, marketers use nine different channels and platforms to market to prospects. As companies expand or reduce their tech landscape, they are often left with incoherent accounts that keep disorganised data.

Customer data can sprout from anywhere, as sales transactions and customer interactions are trapped in a company’s CRM and EPR systems. Then, some external data providers offer customer information to help marketers in lifecycle journeys and managing customer purchase lifecycle.

If businesses want to succeed, they need to structure, organise and analyse data to drive their marketing strategy and use it effectively to engage customers. These are the steps that will tell you how organised data can help in improving your marketing strategy.

Simplify and streamline customer data

It has no purpose to own large amounts of data if you can’t interpret it and make it work for your benefit. Departments have to create a blueprint of their marketing technology stack so that they know what is being monitored, what data is being produced and what information they can analyse from relevant tech solutions. The online gaming industry, especially the online casino market has set an example on how a structured customer data pipeline can help in improving gameplay, offers and overall experience. The operations and platforms of online casino services are quite different from the days when we’ve associated casino games only with land-based venues. Make sure to check out SlotsWise.com to read more about various gaming providers and how they tailor their offers with the help of data.

Streamlining your advertising and sales processes will help you to figure out the tools you need to derive insights from your data and form the analytics foundation. Ensure that your data is of high quality and from a reliable source. Think about it – there’s nothing worse than sending personalised, tailored content containing the wrong information about the campaign. Your customer data must be sorted into multiple segments, depending on your leads and who you’re targeting for the ultimate level of personalisation.

Align company goals and KPI’s with data and marketing

There has to be transparency around business goals so that different departments can collaborate and align with the management team to build a quality pipeline. Ultimately, the end goal will be to drive revenue but with building strong, nurturing relationships with clients.

To convert and nurture leads into loyal customers, experts should agree on which factors define a good lead and how to categorise and tier prospects.

When you’ve created the lead structure to capture and convert customer data, it’s time to define KPI’s. KPI’s can be strategic (insights about revenue and profit) and tactical (answering “how” questions on email open rates, clicks, conversions, SEO, etc.).

The primary principle is how you tie tactical analytics to create data journeys, or precisely, how will you improve the effectiveness of your channel. Customer engagement is the largest and most meaningful data segment of a company. Each user has a different number of engagement rate across other channels. The primary purpose is to build, present and drive such engagements to increase the probability of customer conversions. Data-driven marketing has become an important strategy to consider as part of the campaign thanks to the advancements in technology and analytics, allowing to interpret data in detail.