7 easy ways to fight the data sprawl

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Data. It is the foundation for decision making in many successful companies around the world, and one of the most valuable assets a business can have. So far, very familiar.

However, not all data – or data aggregation strategies – are created uniformly. In today’s digital economy, businesses need to know the difference Good Data and Bad As important as data is, they need to know how to manage and use it effectively to bring out the best customer experiences.

For companies that are not equipped with this knowledge, this opportunity is still largely unused.

During the epidemic, online channels became essential for the survival of millions of businesses. Many quickly moved to a digital-first strategy, in which huge waves of first-party customer data – that is, data about their own interactions with their own customers – began to wash over their shores. Despite having no idea how to manage this attack, a resource that could completely transform the customer experience and turbo-charged sales was left unused and unpleasant.

Many businesses are still not ready for the full volume of first-party data that goes their way as new customer channels launch. Unprocessed, untidy and unorganized, the data gives no value to the organization and begins to spread. Not only is this a huge opportunity lost, but the problem can be even more costly if left unchecked.

Sorting it out can be a daunting task. So where should companies start?

1. Understand what makes good data

Good data is the basis of every positive customer experience. Therefore, before undertaking any kind of data initiative in your organization, it is important to understand: what exactly Good data,

Good data is first party data. First-party data is 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 reliable. That is the secret behind the success of most customer-first companies. It allows you to provide highly personalized, valuable experiences for your customers.

There are other considerations in terms of good data. You have to make sure that your data is not fragmented – that is, you are getting a unified view of your customers instead of having different data in different formats for different parts of the customer journey. So, make sure you are connecting all the points as a first step.

Another consideration is standardization – for the data to be useful, you don’t want to compare apples with oranges. So, make sure that whatever form you are collecting data in, you are consistent throughout the stack, so that you can properly measure and analyze it.

Once your data is in usable condition it is also a good idea to divide it by different criteria so that you can reveal the pattern in statistics. For example, cutting it through demographics, past spending, and loyalty may reveal interesting trends that you wouldn’t otherwise find. For example, you might want to look at the characteristics of customers who have stopped doing business with the company in order to reveal the general underlying elements of their journey. Or similarly, segment your highest-spending customers to understand the similarities in their profile.

2. Plan to fight data spray

Just collecting data is not enough – you need to understand what your data suggests and keep in mind the ultimate goal for that insight, so the first step is to plan with a clear direction of travel. For example, is the goal to identify the most valuable customers? Is it to measure and then improve the customer experience at different stages of the customer journey? Do you have to use information about your customers to better personalize your communication? Or really, is it a combination of many goals?

There is 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 are using it for, you can map out all the technical requirements and think about where you can get this information. ). You can also keep in mind all the areas of your business that you want to access and extract value from when you are planning your business.

This planning stage also gives you a solid foundation for strong data governance policies and processes – a way to streamline cluttered data chaos and avoid future entanglements.

3. Think ahead

You will be able to predict more than expected when estimating equipment, data warehousing storage space and the processes your business will need in the future. After all, if you’re worried about the amount of data coming in the door today, think about how much more you’ll transact in two years once your customer base grows.

A tip for discerning people: pay attention to data inconsistencies as you scale – this usually increases as you add more data sources and tools.

4. Lean towards your base

A strong backbone is essential for successful data architecture. It is also here, at the very base of your stack, that you can solve a lot of basic problems that could otherwise snowball into a big headache.

Centralized infrastructure such as the Consumer Data Platform (CDP) can help you establish a source of truth for your first-party data. This gets rid of the silos – which have all the potential for clutter – and ensures that the data you keep is stored in an accurate, up-to-date and uniform format.

If you take this step properly, your data can be used more widely in different departments in your organization. And because you will have a clear picture of what data you have and how it is collected, it will be easier for you to maintain compliance with data privacy rules.

5. Prioritize safety and compliance

If you are sitting on a data sproll, chances are you have no security for threats, security incidents and other unforeseen attacks. There are a growing number of rules that businesses need to follow when it comes to data (consider GDPR, HIPAA, CCPA). So in reality, taking the above steps to understand, consolidate and maximize your data will not only give you measurable ROI when it comes to marketing and sales results, it will also help you in the long run when it comes to compliance.

For example, the GDPR commands that the data of European consumers should be collected only for specified and legitimate purposes, so you really need to make sure that your data collection includes consent. Similarly, having a solid data infrastructure also helps to ensure the accuracy and consistency of the consumer data collected by consensus, which is again another principle 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. This really needs to underpin any data strategy you’re working on.

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. Safety is everyone’s responsibility, so make sure you bring it into your company culture through regular training.

6. Build for flexibility

The number of existing solutions for storing, managing and analyzing your data almost competes with the data you are trying to deal with. The truth is, it’s always hard to evaluate what tools will grow with you over the next two months, compared to what tools you will grow over the years.

Don’t let that drown you. The main thing to avoid is buying in 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 that your reality matches the standards and policies you set as part of your data governance strategy.

If there is no explicit use of the data that your teams are storing, make sure you delete it or move it to Data Lake to make it easier to store and sort. Better yet, don’t capture it in the first place – a radical move that could make a big difference in the fight against data spread.

Control data spray

The expanding mess of raw data is at best a useless resource and at worst a real obstacle to your company’s success.

While daunting at first glance, 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, accepting and controlling your first-party data is something you can’t do without.

Katrina Wong is the VP of Product Marketing in the Twilio segment,

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