For years, third-party data has been the mainstay of digital marketing, but today’s highest performing companies are increasingly looking internally, to their first-party data.
Better customer experiences demand better data. Brands have to understand individuals and audience patterns – channel interactions and their role the customer journey – what customers want and when they want it. In every case, first-party data from real customers is going to be the most useful.
The opportunity is unique because first-party data is defined, collected and owned by the brand itself. The data can be more accurate and timely than that from external sources and it’s useful for short-term action as well as long-term benchmarking.
This research is based on an online survey of over 300 senior marketers at organizations using at least two of the three categories of data (first, second and third-party).
Companies have been investing heavily in data as its role in digital marketing grows. Looking back on those investments, respondents were able to compare how different categories of data perform for various goals.
The issue, then, is availability. Third-party data is a necessity to fill in gaps in what we know about the customer today. The secret for high-performing companies is a model that takes advantage of all three categories of data, while working to maximize the owned, first-party component.
The future of marketing is using technology to provide uniquely human experiences by identifying what brands can do to add value to customer’s lives. The majority of survey respondents believe that first-party data is how they will win the battle for customer understanding and engagement.
To help marketers plot their course, the report examines differences between mainstream companies and those with high-return data initiatives. Comparing these high-performers with the rest, there are differences in investment and outlook.
Most striking is how those with high-ROI initiatives organize their data practice. They are much more likely to have plotted a long-term data strategy (44% vs 16%) with measurement processes agreed upon and in place (44% vs 16%).
High-performers are also significantly more likely (37% vs 11%) to match their data strategy with sufficient staffing to power it.
The key message from leaders is that they’re listening to their customers by collecting first-party data wherever they can and putting it to work.
The data-driven marketing revolution is in full swing. Despite a predictable media backlash to the overuse of terms like “big data,” every tangible business indicator suggests that the role of data in marketing is already firmly established and can only grow.
We will see that for the organizations we studied, data is the foundation of their customer relationships today and strategies for tomorrow.
To best explore how marketers are using data, this report highlights the differences between top performers and the mainstream. The contrast between the 36% seeing “strong positive impact” from their data-related marketing investments and the rest of the sample is significant, consistent and illuminating.
The divide is not between the companies achieving strong ROI and those failing to produce results with data (only 11% of respondents). Rather it is with those companies that see some positive impact, but have further to go. This group makes up nearly half of the sample (47%) and is in position to take advantage of the lessons of the leaders.
It’s important to note that the companies reporting the best return on their investments are significantly more likely to be using first and second-party data than their peers, with a smaller but notable difference in their use of third-party data.
The rest of the sample resembles industry averages, with roughly 70% using first-party data and nearly 60% taking advantage of third-party sources.
Successful data-marketing practices are using more varied types of information and engage with more sophisticated models, such as those using behavior and partner data.
First, this means that those organizations simply know more about their customers, and conversely the impact of their own marketing.
Second, the “high ROI” companies are learning and optimizing. They’re building their understanding of what the data means, and developing processes to improve collection as well as to speed analytics.
Over time, these activities lead to an institutional comfort and skill in using data for tactics and strategy. Many organizations like to claim that they are “data-driven” but the reality is usually murky because there isn’t sufficient trust and facility with the data.
Figure 3 describes how commonly some are used by respondents. Transaction history and customer information are the most commonly used by all respondents.
These first-party data types are complemented by customer data from trusted partners (second-party data) at 63% of organizations with strong data-related ROI, but less than half of the mainstream. Demographic customer information is the most commonly used form of third-party data.
Typically this would include geography, age, income, education and family status. Behavioral data predicts future interests and events. For example, multiple visits to similar content can narrow the focus of content delivery.
Behavioral results vary, due to the complexity of modelling action and intent beyond the most basic associations.
Third-party customer and behavioral data include many different slices of information, including such diverse information as individuals’ past purchases, intent and their buyer segments (“Boomer” vs “suburban Dad” for example).
First-party data is free and unique. It is also unfettered by rules or partnerships except when they’re voluntarily adopted by the brand.
But the most important advantage of first-party data is that it offers the kind of insight that gives brands real control over their commercial destiny. Data from outside sources can improve the short-term performance of marketing, but it can’t explain the relationship with customers and their paths to purchase.
Before companies can take advantage of the data they already own, they have to collect it. In Figure 4 we see that there is a gulf between the respondent groups in how and where they access their first-party data.
The first-party data resource is largely untapped. Even top-performing organizations are not taking advantage of the whole slate of sources for proprietary customer information. Some are of particular value for their uniqueness, their potential or because they’re produced within a channel of growing importance.
1. The greatest source of data to digital marketers may not be digital (yet). Through the vast majority of revenues are generated offline, there’s a gulf in understanding of how the digital and traditional worlds interact and affect each other. Data from offline sources/point-ofsale can bridge that gap.
2. At many companies the richest customer dataset is hidden in plain sight. Email/SMS databases include vast amounts of rich, reliable data that goes back to the beginnings of an organization’s digital marketing efforts.
3. Traffic from mobile devices is growing by double digits every year. No sector is immune and brands are scrambling to provide effective mobile customer experiences. Yet, fewer than 50% of respondents are taking advantage of the data produced by mobile web/application channels. Gathering data from sources beyond the website is one way that leaders differentiate themselves; their data is more likely to reflect the real world’s diversity of devices and channels.
4. For many brands, the most important customer interactions happen at call centers. They are often where new accounts are initiated and where problems surface. Smart brands invest in automation, systems and training to improve their selling and service, but only about half collect the rich data being produced.
5. Even among large organizations, few brands currently have initiatives to use data from beacons and sensors. Roughly one-in-four high ROI companies is active in this area, but the number drops to less than 10% for the mainstream, figures that will inevitably rise, sharply in many sectors. The potential for this type of first-party data is enormous because it captures aspects of customers’ lives in detail.
For companies that already use these channels but don’t take advantage of their data, next steps are clear:
1. Conduct a data audit to identify what data is currently being generated, how it’s being measured and the gaps between the two.
2. Create a data strategy that looks ahead while providing practical, meaningful guidance to all levels in the organization.
3. Consider data governance and create policies to clarify how data is defined, used, stored and shared.
4. Plan for long-term measurement and benchmarking based on owned data. For those that do not yet deploy these or other channels, the potential value of the owned data they can produce should be factored into the decision making process.
When respondents were asked to assign different categories of data to desired outcomes, first-party data is the top choice. Roughly two-thirds of the sample selected it across each success measure.
Campaign lift is the short-term manifestation of data-driven marketing. Improved targeting, optimization of content and device recognition are just some of the ways modern marketers are able to make improvements to performance. Customer data is clearly more powerful for these activities, with 92% choosing first or second-party data. The issue, then is availability. For many organizations, third-party data is a necessity to fill in large gaps in insight.
Taking a longer view, marketers also look to direct customer data (95%) to increase customer lifetime value. This practice is a function of more than one campaign or purchase; it’s the result of a customer’s whole experience from “meeting” the company to leaving it. First-party data is unique in its role here because the customer’s individual file should be the most powerful tool in adding value to the customer and extending their relationship with the company.
Accurate customer data is the key to insight, enabling these other capabilities. Nearly 75% of all respondents cite first-party data as generating the greatest insight, with another 18% looking to the first-party data of their trusted partners.
That insight powers digital marketing, driving success across metrics like campaign lift and customer lifetime value. As a result, nearly 70% of respondents agree that the case for first-party data is the easiest to make.
In Figure 5 (above) we saw that first-party data is the first choice among marketers for customer insight and that it has the greatest impact on customer lifetime value (CLV).
That strong preference is partly because first-party data is the purest fuel for some important emerging capabilities in the marketer’s arsenal. Companies with profitable data-related marketing practices aren’t just doing more of these, they’re practicing them more successfully.
All three categories of data can support these activities, albeit in different ways. But in the long run only first, and to some extent second-party data, can be used to build useful models and accurate benchmarks. Internal data is obviously more specific, but it’s also more reliable over the long term and should ultimately be more accurate than other options.
Content personalization is a central piece to tailoring customer experience. It will only become more important as the role of mobile increases. Limited real estate means taking advantage of every pixel and moment by delivering specific content quickly enough to still be useful.
Marketing attribution is one of the most complex challenges facing marketing today. It’s an attempt to bring sense to a world where everything is fragmented, from media consumption to device usage to the role of individual channels in the tapestry of customer behavior.
The first-party data produced by each channel is the essential ingredient to attribution and to understanding the customer journey. Companies with centralized command over these siloes of information have an enormous advantage and are able to move more quickly and accurately down the path to understanding their customers, and how marketing affects them.
The greatest threat to using owned, internal data to drive marketing may be a lack of trust. Unless organizations can rely on their numbers and what they mean, learning is inhibited and data never makes the leap to information and ultimately knowledge. Figures 7 and 8 highlight this issue and how it affects marketing organizations’ use of the different data types.
Compared to the digital marketing industry as a whole, respondents to the First-Party Data Study are larger and somewhat more sophisticated in their data use. All respondents take advantage of at least two categories of data and as a group they’re further along in building capabilities such as marketing attribution and customer journey analysis.
Despite these advantages, they still contend with some of the fundamental challenges in data acquisition, management and analysis.
The first lesson is that the organizations with the most success in using data are also accurately aware of their limitations. Those with strong ROI are more likely to describe their efforts in data as “ad hoc” and lacking strategy.
They’re also critical of their data quality and availability, the top issues for all respondents.
At first glance, quality would appear to be a more pressing issue with data from outside the enterprise, but that’s not always the case. In fact, several types of first-party data get a somewhat lower score for accuracy in Figure 8. While counterintuitive, there are a number of reasons that organizations might find it easier to trust outside sources than their own.
One issue is data hygiene. How it is categorized, cleansed and processed from collection through analysis is an essential part of data management. Often, errors are introduced in the routine procedures through which it is generated, stored or used. For example, some types of data (like CRM and point-of-sale information) are particularly prone to entry errors because they rely on human beings.
Recency and accuracy issues can also arise as data ages or as it’s passed from one system to another. Few organizations are immune; marketers themselves estimate that roughly 20% of their contact data is bad for one reason or another.
But in most cases, the raw quality of in-house data should be significantly higher than that of third-party sources. No database is perfect, but internally produced data is generally far more reliable than aggregate information because the marketer is in control.
The answer may simply be that it’s easy to overlook quality issues in outside data, while discrepancies in first-party data are more obvious.
Marketers and their agencies have a multitude of tasks to complete on tight schedules. So long as the data they’re using is perceived as accurate enough to accomplish their goals, there’s little incentive to dig deeper.
Across the entire sample, marketers plan on increasing their use of first and second-party data. Only in the case of third-party data do less than 50% of respondents project an increase, according to Figure 9 (below).
Marketers’ evaluations of the importance of different data types mirror their expectations moving forward. First-party sources rank most highly, with transaction history and CRM cited by the vast majority of respondents. Second-party data follows, with third-party sources taking the bottom spots, all comprising roughly half the sample.
To take full advantage of data – especially their own first party data – marketing leaders have to contend with key challenges related to process, policy and human resource. Companies with strong positive returns on their data investments are far more likely than other organizations to have the processes and people they need to effectively utilize their data resources.
First-party data strategy should start with business goals. It’s only in the context of the larger enterprise that data can be used to its potential. The impact of first-party data, for example, can extend into every part of the organization, from guiding product development to identifying market trends to informing financial projections.
The best strategies help people make decisions accurately and quickly. They guide leaders by clearly defining top priorities and the entire organization by describing the paths to achieve them. As companies expand on the goals for data, their strategy should address how it will collected, stored, shared and managed over the short and medium term.
Data management and measurement policies are essential to trust, because they define what is being measured, and how. They typically include rules about how data is accessed and shared as well as how it is described.
Some of the most important decisions in the policy-making process will be around customer records. For example, how will records be scored and used over time as new pieces of information are added and others lose their immediacy, as in the example of purchase intent?
Human resourcing for data-fueled marketing is an issue across the sample. Even among top performing companies, only 37% agree that they have sufficient people and skills to fully power their initiatives. Staffing data initiatives is most challenging for those organizations that haven’t put the other pieces together; a clear data strategy informs the need for overall resources and new capabilities. It also defines the opportunity around data initiatives, helping make decisions about training existing staff, hiring new team members and using outside partners.