Customer data is a game changer for new D2C players

The switch to D2C can bring numerous benefits for companies. Higher margins and the opportunity to increase sales are undoubtedly enticing. However, one of the biggest benefits is customer data. When used properly, it can revolutionize the way you do business and interact with customers. The return on investment is then just icing on the cake.

For many manufacturers, the main motivation driving them toward the D2C model is the financial benefits, including the opportunity for higher margins and increased sales. Manufacturers are less and less willing to give a large portion of the final price of their products to middlemen. And they usually have to pay extra if they want the retailer to set their product apart from competitors.

But that’s not all. Even when planning how to achieve a satisfying return on investment and higher profits, it quickly becomes obvious that the key to success and one of the greatest benefits is the customer data you get with D2C.

Get your customer data

In the traditional B2C sales model, manufacturers typically do not interact directly with consumers and thus have no opportunity to collect data on their behavior. If they need information about customers, their preferences or attitudes towards the brand and its products, they usually commission market research. Optionally, they can attempt to obtain the required information from retailers. But again, they often have to pay extra for this.

And even if distributors and retailers are willing to share customer data with manufacturers, there are legal restrictions, because they have to first obtain permission from each individual customer. This has become even more challenging with the tightening of data protection legislation in recent years.

With D2C, this is different. In this case, manufacturers gain more control over every step of the sales and customer support process, which gives them an invaluable resource — vast amounts of data about their customers and their behavior.

D2C requires a new approach to data management

The reality is that most companies that sell through distributors and resellers have little experience managing large amounts of customer data.

Of course, every manufacturer collects information about its B2B customers. But for one thing, this information is largely of a different nature than what is collected about retail customers, and secondly, both the number of buyers and the volume of data are vastly different.

The data of a few hundred or even a few thousand business clients can be managed without engaging advanced and often very expensive IT systems. Additionally, much of the communication with clients takes place through personal interactions. Therefore, you usually do not need sophisticated tools and integrated systems to automate the entire customer relationship.

The situation changes dramatically when you switch to D2C. Suddenly, the number of your customers is in the tens or hundreds of thousands, or even millions in the case of consumer products. The amount of data you need to collect and process on an ongoing basis to maintain continuous customer service grows exponentially every day. Even greater is the amount of data that you do not need to fulfill orders and provide customer support, but can use for other purposes, such as personalization.

The journey from data collection to turning data into actionable insights is multi-faceted and involves many aspects that you should consider in your data strategy. Let’s discuss the most important of them.

Providing engaging interactions

The type of data you collect and how valuable it will be for your business will largely depend on the amount and type of interactions you offer on your e-commerce portal.

Of course, you can simply use a standard online store template and observe your customers’ behavior. However, this will not allow you to fully exploit the potential of the online channel. It is definitely worth coming up with your own ideas for interesting features and interactions that will further enhance the customer experience and set you apart from your competitors.

In this way, you can obtain what is known as “zero-party data” in addition to transactional, behavioral or geolocation data. This is all kinds of information about your customers that they provide you with on request or on their own.

Sometimes it is easier to ask the consumer directly about their preferences. For example, giving them the opportunity to rate product images with one click (thumbs up or thumbs down) saves you the trouble of analyzing them later.

Today’s consumers are aware of the value of their data, so D2C companies need to provide them with a real benefit to get them to share not only their personal data but also other information. You can achieve this with things like gamification or other fun elements, but most importantly you have to give the customer tangible value. This could be in the shape of a more attractive shopping experience, more relevant product recommendations or content that is better tailored to their expectations.

Data capture

Once you know what data you want to gather and how to get it from your customers, you need to learn how to collect it.

For quantitative and highly structured data like personal information and differing preferences, it is easy: customers provide you with many of these when they register, subscribe to a newsletter, place an order or fill out surveys.

This information is very important for order processing and ongoing customer service, but it is less relevant when you need more detailed information about a customer’s changing habits, expectations, attitude toward the brand, product sentiment or willingness to buy.

Such insights can be derived primarily from behavioral data. Therefore, you should monitor all customer activities in your online store in real time. While some of these interactions, such as clicks, leave permanent traces in your IT systems, for many others you need special methods and tools to capture them.

With the appropriate technical solutions, you have countless options. The only limitations are legal issues related to privacy.

Data protection and compliance

When dealing with customer data, there are strict data protection regulations to be observed – first and foremost the GDPR. It becomes particularly challenging with international activities that even go beyond the EU. Not only that you have to observe more and more regulations for this. The restrictions are also becoming increasingly stringent.

In the end, virtually nothing runs without the customer’s consent. In addition, users must be able to review and edit their data and revoke their consent. Therefore, the legally compliant collection and management of data is certainly a major challenge.

Data integration

Your e-commerce portal is just one of many sources that generate customer data. In practice, every sales and customer service channel will be another source of potentially invaluable information. Additionally, a huge amount of data is being collected in your organization’s backend systems, especially in ERP and CRM. On top of that, there are also external sources such as social media, data brokers, data aggregators and analytics platforms.

Moreover, data in all these separate systems can be structured, semi-structured or unstructured and come in a wide variety of formats, such as electronic documents (DOCs, PDFs, TXTs), email or online chat messages, phone call recordings, photos, videos, etc.

So, if you want to make accurate data-driven decisions, you need to create a single consistent source of truth for all your customer data. A natural step in such consolidation is to ensure that your data is of high quality.

Want to know more about data integration? Click here!

Data quality

When information comes from multiple, disparate sources, various data quality issues almost inevitably arise, such as untrustworthiness, inconsistency, duplicate records, inaccurate, incomplete or outdated information. And the more data you collect, the more problems you have.

Most data quality issues occur when information is entered manually by people, be it customers or employees of your company. That’s why it’s very important to properly design all functions used to collect data and equip them with tools to verify data correctness, such as field validation, condition rules or auto-completion.

But that will not protect you from all difficulties, especially when migrating data from many different systems into a central repository. That’s why you need to develop a holistic framework for improving data quality.

This kind of data quality management system allows you to continuously monitor all aspects of data quality, identify issues and fix them in a highly automated manner. Since many errors are of similar nature and have the same causes, you can eliminate them relatively easily using predefined data quality rules. The most difficult cases, hard to resolve automatically, can still be handled by humans.

Click here if you would like to learn more about how you can ensure data quality in your organization.

Data analytics

Once you start consolidating data in a central repository and provide an automated data quality management system, the next step is data interpretation. For this, you need to professionally analyze the data so that you can systematize the knowledge you collect and draw valuable conclusions. These then help you take further decisions and actions.

You can start with general analytics to better understand your audience, identify typical customer journeys or verify your own hypotheses.

Incorporating machine learning into your data analysis further increases its value. With it, you can identify behavioral patterns with which you can define customer profiles and marketing campaigns in more detail, or significantly improve the user experience in your online store.

The more customer data you have at your disposal, the more accurate insights and conclusions you can get.

With a sufficiently large volume of data and a broad spectrum of information collected, you will be able to apply advanced analytics to even anticipate the future behavior of your customers.

With predictive analytics, you can not only identify new opportunities and better meet the needs of your portal’s users, you can also more effectively prevent potential crises and customer losses.

Turning data into action

Collecting and analyzing data is meaningless if you do not have ideas on how to use the resulting insights. What you really want is for the data to have a measurable impact on your business.

One of the main ways to achieve this goal is to leverage insights from data analytics to improve the customer experience, including personalization of the e-commerce portal.

It is up to you how much personalization you want in your online store. You can start with simple tricks, such as reminders about recently viewed products or displaying content that matches the customer’s interests, and then implement more and more advanced mechanisms that enable in-depth personalization of virtually all elements and content.

Looking for ideas on how to personalize your e-commerce platform? Download our free e-books!

What matters most is your response to customer behavior in the here and now. For this you need to provide real-time personalization and react immediately while the customer is browsing your online store.

Once you start taking data-driven, real-time action, keep studying your customers’ responses and collect feedback. This is a continuous cycle where each new piece of information allows you to further improve the customer experience.

Technology is the solution

To create a personalized customer experience based on data analytics, you need an integrated environment equipped with the right tools to address each of the above aspects.

When you start D2C, you are suddenly overwhelmed with data. Then you need a mechanism that ingests and integrates data from various sources, ensures its highest quality, analyzes the data, provides insights and conclusions, and finally personalizes communication and the customer journey.

You can of course assemble such a complex solution using individual components (applications) responsible for different areas. Alternatively, you can use a comprehensive platform solution equipped with all the required modules that perform individual tasks.

Customer Data Platforms (CDPs) are one of these solutions. They not only consolidate and cleanse data from different sources to create a complete 360-degree customer view, they are also equipped with many other functionalities you will probably need. These include functions for GDPR-compliant data management, reporting and data analytics, process and marketing automation, and predictive analytics.

The fact of the matter is that if you have no experience with such technologies, you will not be able to figure out what software you actually need. And then there are the many other topics you have to deal with, such as implementing, configuring, customizing and integrating new tools with existing systems into one cohesive and maximally automated environment. These are not trivial tasks, so the help of an experienced IT partner can prove indispensable here.