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Data. It’s the foundation for decision-making at many of the world’s most successful companies, and one of the most valuable assets a business can hold. So far, so familiar.

However, not all data — nor data collection strategies — are created equally. In today’s digital economy, businesses must know the difference between good data and bad data. Just as importantly, they must also know how to manage and use it effectively to bring about amazing customer experiences.  

For companies that aren’t armed with this knowledge, this opportunity is still left largely untapped. 

During the pandemic, online channels became essential to the survival of millions of businesses. Many had to pivot rapidly towards a digital-first strategy, with huge waves of first-party customer data — that is, data about their own interactions with their own customers — starting to wash up on their shores. With no idea how to manage this onslaught, a resource that could completely transform the customer experience and turbo-charge sales was left unused and unloved.


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Many businesses are still unprepared for the sheer volume of first-party data that heads their way as soon as a new customer channel is switched on. Unprocessed, uncleaned and unorganized, the data delivers no value to the organization and begins to sprawl. Not only is this a huge opportunity lost, but the problem can become even more costly if it’s left to fester. 

Sorting it out can feel like a time-consuming task. So where should companies start? 

1. Understand what makes good data 

Good data is the backbone of every positive customer experience. Therefore, before undertaking any sort of data initiative within your organization, it is important to understand: what exactly is good data?

Good data is first-party data. First-party data is the data that you collect directly from your own customers, with their consent, about how they use your products and services. Unlike third-party data, it is clean, accurate, and trustworthy. It is the secret behind the success of the most customer-first companies. It allows you to provide highly personalized, valuable experiences for your customers.

There are other considerations in regards to good data too. You have to ensure that your data isn’t fragmented – i.e., that you’re getting a unified view of your customers rather than having disparate data in different forms for different parts of the customer journey. So, make sure you’re connecting all the dots as a first step.

Another consideration is standardization — for data to be useful, you don’t want to be comparing apples to oranges. So, make sure that whatever form you’re collecting data in, you’re consistent across the whole stack, so that you can properly measure and analyze it.

Segmenting your data by various criteria once it’s in a usable state is also a good idea so that you’re able to reveal patterns in the statistics. Cutting it up by demographic, previous spend and loyalty, as examples, can reveal interesting trends that you might not find otherwise. For example, you might want to look at the attributes of customers who stop doing business with the company to reveal the common underlying elements of their journeys. Or equally, segment out your highest spending customers to understand commonalities across their profiles.

2. Make a plan to fight data sprawl

Simply collecting the data is not enough — you need to understand what your data signifies and have an end goal in mind for those insights, so the first step needs to be making a plan with a clear direction of travel. For instance, is the goal to identify the most valuable customers? Is it to measure and then improve the customer experience across different stages of the customer journey? Is it to use the information you have about your customers to better personalize your communications? Or indeed, is it a combination of several goals? 

There’s also the question of your audience, which will play a big part in what your data goals should be – is it the CMO and the marketing team? Sales? Customer service leaders?

Once you know what you want from your data and who you’re using it for, you can map out all the technical requirements and think about where you can source this information from (whether customer service interaction history, marketing campaign open rates or something else). When you’re building out your plan you can then also bear in mind all the areas of your business that you’ll want to access and extract value from it. 

This planning stage also gives you a solid basis for robust data governance policies and processes – a way to bring order to the chaos of unmanaged data, and to avoid getting caught out in the future.

3. Think beyond big

You’ll do well to forecast more than you expect when estimating the equipment, data warehousing storage space, and processes your business will need in the future. After all, if you’re concerned about the volume of data coming in the door today, just think how much more you’ll be dealing with in two years’ time once your customer base has grown.

A tip for the wise: pay attention to data inconsistencies as you scale – these usually increase as you add more data sources and tools. 

4. Tend to your foundations

A strong backbone is essential to a successful data architecture. It’s also here, at the very foundation of your stack, that you can solve a lot of the basic problems that might otherwise snowball into bigger headaches.

A central infrastructure like a Customer Data Platform (CDP) can help you establish a single source of truth for your first-party data. This gets rid of silos – with all the potential for chaos that they entail – and ensures all the data you hold is accurate, up to date, and stored in the same format. 

If you get this step right, your data can be used more broadly within your organization across different departments. And because you’ll have a clear picture of what data you hold and how it’s collected, it will be far easier for you to maintain compliance with data privacy regulations.

5. Prioritize security and compliance

If you’re sitting on a data sprawl, the likelihood is that you haven’t got any protection in place for threats, security incidents and other unexpected attacks. There are increasing numbers of regulations that businesses need to comply with when it comes to data (think GDPR, HIPAA, CCPA). So actually, taking the steps above to understand, unify and make the most of your data will not only provide measurable ROI when it comes to marketing and sales results, it’ll also help you in the longer term when it comes to compliance. 

For example, GDPR mandates that European customers’ data must only be collected for specified and legitimate purposes, so you really need to ensure that consent is built into your data collection. Equally, having a solid data infrastructure in place also helps to ensure the accuracy and relevance of that consensually collected customer data, again another tenet of GDPR.

Above all it is important to take security seriously and ensure that you, your partners, and suppliers all have comprehensive data security practices and compliance certifications in place. This really needs to underpin any data strategy that you’re working at.

While you’re at it, remember that technology and processes are just two key components of an effective security program. The third is your team. Security is everyone’s responsibility, so make sure you bake it into your company culture through regular training. 

6. Build for flexibility

The number of solutions that exist to store, manage, and analyze your data almost rivals the volume of data you’re trying to deal with. The truth is, it’s always hard to assess which tools you’ll outgrow in the next two months versus the ones which will grow with you for years.

Don’t let that overwhelm you. The key thing to avoid is buying into a closed software suite that locks you into a specific set of tools, as this will limit your ability to adjust as your needs evolve.

Most companies switch tools in and out as their priorities evolve. By planning for this kind of flexibility, you won’t get stuck with legacy technology that limits your future data potential.

7. Audit, audit, audit

Regular data audits ensure your reality matches the standards and policies you’ve laid out as part of your data governance strategy. 

If there’s no clear use for the data your teams are storing, make sure you’re either deleting it or moving it to a data lake, to make it easier to store and sort. Even better, don’t capture it in the first place – a radical move that can make a huge difference in fighting the data sprawl.

Take control of data sprawl

A sprawling mess of raw data is at best a useless resource, and at worst a genuine hindrance to your company’s success.

Although daunting at first sight, its true potential can be unlocked with thought and structure, helping you understand your customers and dramatically improve the performance of critical aspects of your business.

In today’s competitive, digital-first environment, embracing and taking control of your first-party data is something you can’t do without.

Katrina Wong is VP of Product Marketing at Twilio Segment.


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