The Ultimate Guide to Data Quality Welcome to Latana’s Ultimate Guide to Data Quality! It’s very likely that you’ve heard someone say that branding campaigns are all about gut instinct and that there’s no way to track their performance or measure their success. Well, we’re here to tell you that’s categorically false. And if you’ve gotten this far, it’s safe to assume that you know this isn’t true as well. Measuring your brand’s health is an essential process for marketers and brand managers striving for growth — and can be a powerful tool to help iterate campaigns aimed at improving awareness of your brand or changing how consumers perceive it. Without business intelligence like brand tracking, you’re just shooting in the dark with no real way of even knowing if you’re hitting your target or not. But, as with any type of campaign, the quality of the insights that your strategy is built upon can be the difference between success and failure. This is why data quality is an essential consideration. In this guide, we’ve compiled everything you need to know about maintaining the highest data quality standards, with a focus on how it is achieved in brand tracking. We’ll also cover exactly how you can use the insights gained from your data to unlock growth. So, let’s dive in! Table of Contents Data Quality: The Basics How To Define Good Quality Data Why Data Quality Is Important Using Data Responsibly How To Maintain Data Quality Three Tips For Maintaining Data Quality How Latana Maintains Data Quality When Brand Tracking How Latana Collects Reliable Data From Consumers How To Get The Most Out Of Your Data Brand Tracking KPIs Explained How To Use Data To Power Campaign Creatives Conclusion What’s Next? C h a p t e r 1 C h a p t e r 2 C h a p t e r 3 Data Quality: The Basics C h a p t e r 1 Data Quality: The Basics C h a p t e r 1 The most important thing to establish first is that, when investing your time and resources into analytics, it’s vital that you ensure the data you gain from it is trustworthy. Indeed, low-quality data can be just as damaging as having none at all. And, in some cases, more so — especially if it leads you to fundamentally misjudge the marketplace or gives you a false understanding of how your business is performing. How To Define Good Quality Data So, what separates good data from bad data? There are five pillars of good quality data, and ensuring that you meet these five criteria is the best place to start: Depending on the type of data that you’re handling, these five pillars will mean slightly different things — especially as there are a variety of different ways that data can be collected, collated, and understood. Therefore, each distinct data set you use may have its own distinct methodology that ensures the highest standards of quality are met. Obviously, all data sets have their own acceptable margins of error, too, but data quality is not about achieving perfection. Ultimately, the goal is to ensure that your data represents reality and is not skewed by errors or biases. If this can be guaranteed, you can safely build your strategies upon the insights gained. Does your data show the full picture? Is the source of the data reliable? Is the information up-to-date? Are the numbers and values correct? Are you consistent in your use of data types, sources, and metrics? Timel ines s Rel iab il it y Accu racy Co mpl etenes s Cons istency By Measuring Campaign Performance, You Can Scale Your Most Successful Campaigns 1. A campaign isn’t really complete until you’ve analyzed its performance and can understand what worked and what didn’t. By doing this, you can continually course-correct as your brand grows — and gain in-depth knowledge of how your target audience responds to a range of different campaign types and messages. For brands on the rise, especially those competing against established names, being able to identify which channels and campaign types bring in the highest value customers is the key to super-charging growth. The tried and tested method is to start off small, iterate with different creatives, optimize based on the results of your tests, and scale up to wider audiences. Here it is essential that your data is accurate so that you don’t waste money on campaigns that are ineffective or scale up a creative that isn’t actually performing as well as you think. For branding campaigns, you can use brand tracking software to see if your efforts have raised awareness, consideration, or preference for your brand in a specific target area — such as a single city — before scaling to a wider market. Why Data Quality Is Important To Unlock Growth, You Need To Understand Your Target Audience 2. It goes without saying that you’ll struggle to grow in a sustainable way if you have no idea who your target audience is. Understanding what motivates your customers or clients is one of the most essential things marketers must grasp because this will help to build a more customer- centric business — which, in turn, will increase the lifetime value of your customers. It’s not enough to just define your own target audience without research. In fact, doing this means you might actually miss opportunities or fail to understand how your product fits into the lives of your customers. Knowing your target audience will allow you to focus your marketing efforts on a smaller, more specific group of people that are more likely to convert. This focused approach can be paired with special messaging that resonates with a specific demographic, such as Gen Z and Millennials, to increase the effectiveness of your campaigns. For example, you might think your target audience is urban Millennials but, through research, could discover that older audiences in rural areas are actually more engaged with your brand — and show a greater preference for it than their younger, city- dwelling counterparts. With this information, you could then shape your offering to fit their needs, too, and provide a strong framework for future growth. Rural Boomers 62% Gen Z 14% Urban Millennials 23% Because your target audience defines so much about how your brand communicates and what values it embraces, you need to be certain that the data used to ascertain who they are is accurate and up-to-date. Indeed, it’s worth remembering that your audience can evolve over time as your brand grows and as demographics age. For example, an increasing number of Millennials are now homeowners, so old assumptions about this generation need to be reassessed. By tracking the evolution of your target audience over time, you can ensure you’re always speaking to them in the most effective way. While you’re still free to target audiences that you believe will benefit from your product or service, high-quality data can give you reliable insights on how well you’re doing and what steps you might need to take to break through with specific target audiences. Ultimately, the more you know about your target audience, the more you can cater your message to them and target them more accurately. Defining Bespoke KPIs Requires Quality Data 3. Key performance indicators, or KPIs, are used by many companies to measure the success of their activities, keeping track of the company’s health and its progress towards pre-defined targets. Many companies track the same KPIs but not all companies are on the same growth trajectory — so, it makes much more sense to create KPIs that are tailored to the unique challenges that your brand faces. This way, you can define your success in a way that fits your offering, industry, or the type of business your brand represents. For growing brands, some KPIs will be more important than others. Keeping track of your brand associations and brand experience as you grow is important to make sure you’re perceived in a positive way — while measuring brand engagement will give you an idea of the type of relationships consumers have with your brand. In order to define KPIs that will help you establish relevant goals for your brand, you need to have reliable data that you can track over time. Without this, you’ll struggle to know whether you’re succeeding or not. Understanding The Current State Of The Market Will Help Define Your Strategy 4. You cannot build your business strategy in a vacuum. The wider ecosystem of the industry in question and your competitors need to be taken into account. Here, awareness isn’t enough to get ahead of them. To gain the edge, you’ll need to figure out what they’re doing and how they’re doing it. Analyzing your competitors can give you powerful insights into how consumers view them and whether their brand has any weaknesses that you can then exploit with your own product offering or with new brand messaging. Ultimately, competitor analysis helps you strengthen and clarify your own value proposition. On top of this, performing market research can provide insights into the size of the overall market and what opportunities there are for growth within it. Perhaps consumers are willing to spend more money than in previous years or are increasingly concerned about topics like sustainability? Growing brands can undermine the dominance of more established players in the same industry by listening to consumers and growing the market in a new direction. Using Data Responsibly A key challenge for brand marketers is to find a way to provide accurate and relevant personalization and use data to power their campaigns — while also protecting and respecting a customer’s right to data privacy. Indeed, consumers are more concerned about their privacy than ever before and regulations such as GDPR and CCPA have already put necessary restrictions on the types of data businesses can store, while empowering consumers to challenge how their personal data is used. Ultimately, when collecting, storing, and using data, there’s an inherent risk involved — unless, of course, you’re using zero-party data. With zero-party data, it’s possible for marketers to capture data that’s shared willingly and intentionally. By collecting and using this data in intelligent ways, you can provide rich, memorable, and tailored interactions for your consumers. To explain, let’s first explain the difference between each data type. First-party data is information collected directly from customers via their behaviors, actions, and interests as demonstrated across your app or website — as well as via subscriptions and lead capture forms. Transactional data, such as purchases or downloads, as well as things like how long someone spends hovering over a certain image or viewing a particular product, are all considered first-party data. First-Party Data Privacy concerns surrounding first-party data are minimal, as you know where it came from, when it was gathered, and how it is stored — plus, you’re in control of how it’s used. The challenge with first- party data is that we have to make inferences about customers based on their behavior, so we’re not getting a complete picture of what a customer’s true intentions are. Second-party data is essentially another company’s first-party data that they share with you. You may purchase access to second- party data sets that represent similar groups of people as your audience segments and use that to inform your marketing activities. Third-party data is information that’s pulled from various platforms and sources, then aggregated and sold on to other companies. Third-party data providers do not have a direct relationship with your customers. You can’t really know where third-party data has come from — or when, where, or how it was collected. Governments and tech companies, such as Apple and Google, have begun to regulate and limit the way customer data is collected, stored, and used — which presents a substantial threat to third-party data. By 2022, more than 85 percent of internet browsers will block third-party cookies. With marketers increasingly unable to access third-party data, and only one-third of customers believing that companies are using their data responsibly, brands must find new ways to gather valuable information about audiences in order to stay competitive and continue to create, segment, and target audiences with personalized brand experiences. Second Party Data Third-Party Data Zero-party data refers to “data that a customer intentionally and proactively shares with a brand, which can include preference center data, purchase intentions, personal context, and how the individual wants the brand to recognize her”. There are a number of inherent bonuses to using zero-party data, aside from that the fact that it is more compelling both in terms of privacy and accuracy. First and foremost, with privacy concerns being minimal, it’s a much more trustworthy way to find out about your customers and tailor your campaigns towards their preferences. On top of this, the insights gleaned from zero-party data are more accurate, as the customer is giving you self-reported information, rather than you making inferences based on their on-page or in-app behavior. Finally, this data is exclusive to you — the second and third-party data that you’re accessing is likely being accessed by your competitors too, so shifting your focus to zero-party data means that you’re working with unique insights captured directly from your customers. With the deprecation of third-party data on the horizon and increasing concerns for data privacy, understanding how to collect and use zero-party data is the key to reducing your brand’s reliance on first and third-party data. Luckily for you, the data that you glean from brand tracking is classed as zero-party data — meaning you can learn about your target audience in a way that respects their privacy and rights. And if you use the insights gained intelligently, you can build direct relationships with your audience and drive impactful personalized experiences across all channels. Zero-Party Data How To Maintain Data Quality C h a p t e r 2 As we’ve already outlined, data from different sources will often have varying methodologies that can be used to ensure the highest levels of quality and accuracy. In this section, we’ll cover some general tips that can be employed to ensure your business is set up to handle data in a way that maintains quality across different datasets. Then, we’ll focus specifically on how Latana maintains data quality when tracking brands’ health and the processes we use to collect data accurately. How To Maintain Data Quality C h a p t e r 2 Collect and Collate Your Data With Care It’s likely that you’ll have multiple sources of data to track a whole range of KPIs, some of which may be closely related. If you’re building a report that relies on different datasets, there are opportunities here for low-quality data to get past your defenses — even if the source is trustworthy. Three Tips For Maintaining Data Quality Within Your Business This low-quality data can emerge from a simple clerical error, can be the result of using multiple, potentially contradictory, or overlapping sources, or combining your own data with those from third-party sources. Ensure that you’re keeping an eye out for data that doesn’t quite match up, that contradicts existing insights, or potentially duplicates insights that you’ve already gained from other sources to eliminate these errors as you collect and collate the data in question. Don’t Cherry-Pick Data This one ties into the data-quality pillar of completeness — as cherry- picking data will result in an incomplete picture. However, this is an easy mistake to make, especially when you have an expectation of what a particular data set is going to reveal. In these cases, you might be unintentionally manipulating the data to reflect your expectations or to show those positive results that you’re desperate to see. So, make sure you’ve double-checked everything and identified any missing factors that might be skewing the results. Train Your Team to Accurately Interpret Data Even if your data is coming from a trustworthy source, there’s still an opportunity for inaccuracies to creep in if your team is not properly trained to interpret it. Ensure that the team handling and managing your data is aware of your data’s baselines, so they can spot outliers and anomalies — and can investigate each data source to root out potential errors. A good example is being able to identify whether an uptick in traffic to your website is the result of real humans visiting or a slew of bots all coming from a single, untrustworthy source. When it comes to tracking the health of your brand, we believe that Latana provides unmatchable data quality compared to the alternatives. By using machine learning technology, we’re able to accurately track a deeper range of audience segments and measure how their relationship with your brand is changing — while also eliminating the biases or skewed results that typically result from analyzing niche audiences comprised of several different characteristics. This contrasts with traditional brand tracking services which often restrict the number of audience characteristics that you can focus on — meaning you’re not getting the complete picture of your target audience and how they perceive your brand. We believe that, in order to gain a deep understanding of your audience, you need to be able to consider all the complex, different characteristics which make your customers who they are. How Latana Maintains Data Quality When Brand Tracking 25 0 25 50 75 50 75