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Using First-Party Data to Bridge Silos in Today’s Ad Platforms

Data-driven marketing has famously helped marketers better the attribution in their advertising. This increased certainty, however, comes mostly on the back of Google and Facebook – a digital advertising duopoly that has offered compelling value for marketers, but also faces increased scrutiny around privacy and data protection. Brands need first-party data to hedge against the risk of changes in their preferred advertising platforms. Generating that data in an opt-in, consent-driven and declarative way won’t just allow brands to overcome the challenges of change – it will also allow them to be even more certain in their data-driven marketing efforts than ever before.

The idea of first-party data being “declarative” is crucial to why brands are slated to benefit more than they do from the data currently available on many ad platforms. While much of the data on a platform like Facebook is declared by the user, much of Facebook’s advertising is also based on behavioural data. What’s more, the data that is declared by the user is often too general for the diverse interests and choices consumers have available today.

Within this context, Conversational AI is singularly capable of gathering these unique data points required to enhance the understanding of consumers, and do it in such a way that allows the consumer to disclose their own sentiments to brands directly. When brands engage with Conversational AI, whether through a chatbot, voice search or other means, brands have the opportunity to learn more about consumers in a natural conversational format, without driving them away from privacy and relevance concerns.

Before understanding how powerful this really can be, however, it’s important to understand what’s compelling about ad platforms like Facebook and Google, how we got here, and how to best build on what’s already available.

Facebook and Google represent a massive share of digital marketing spend for brands, something brands need to hedge against amidst increasing risk. Source: eMarketer.

Facebook and Google represent a massive share of digital marketing spend for brands, something brands need to hedge against amidst increasing risk. Source: eMarketer.

What’s so good about Facebook?

Facebook has been a compelling platform for advertisers primarily because it is simply so powerful at aggregating information on individual users. Users share information about themselves with Facebook in order to interact with content and their peers, and that same information empowers brands to deliver more relevant advertising and offers to them.

For example, let’s consider a campaign a brand might have run in the past. A new skincare product comes on the market and can be perfectly targeted to females aged 20-45 living in sunny regions like the American Southwest. Before Facebook, a brand promoting this product would have to find the right media to buy, whether it’s TV, radio or magazines, look at their regional distribution, demographics and the appeal a particular advertising channel has with their target audience. In the broad scope, this was an effective process, but time- and cost-intensive, and could often be somewhat discouraging to brands looking to offer niche products or test out new offerings.

With Facebook, brands can still do all of the above, but they can also walk into Facebook’s advertising platform, specify age, location and gender, and within minutes start reaching the consumers they required so many weeks or months of planning to access before. If this concept was presented to an advertiser 30 or 40 years ago, they might look at it as a pipe dream. Now, it is commonplace, and something for which so many advertisers can be eternally grateful.

So again, Facebook still offers a compelling place for brands to advertise, but it also has limitations and may not always “spark joy” within the consumer. If Facebook were to one day be forced to stop collecting certain types of data, or be confronted with a mass boycott, brands would also be left scrambling to access the same data – and cost efficiency – that they have come to love, and their business models may have even come to rely on.

Furthermore, while some of the data that Facebook has is “declared”, it is generalized to the consumer, and not to what might be most relevant about a brand to the consumer. First-party data is crucial for brands to hedge against the risks Facebook is facing, but it will also enable brands to get more granular and one-to-one in the type of information they cultivate on consumers – all while doing it in such a way that is more respectful and thoughtful.

 

What’s so good about Google?

Google offers many of the same benefits as Facebook, but the behavioral data it leverages is intent and semantics-based, rather than profile or interest based, and in many ways this offers even faster paths-to-purchase for brands to access in achieving growth.

Consider again, in the eyes of an advertiser 30 or 40 years ago, how much a pipe dream today’s Google might have seemed to be. It’s a search portal that indexes, evaluates and ranks every openly available piece of knowledge on this thing called “the internet”. It’s commercialized, so that when someone is looking to buy a product as specific as “red shoes in denver”, you can advertise to that consumer and only that consumer. What’s more, the variety of formats, ways to advertise to that consumer, and the performance of the platform improve with each search that’d made – a gift to every ambitious brand and marketer.

In the whole process of advertising on Google, brands don’t even need to consider who a consumer is or what their interests are. Although those qualifiers do help in refining campaigns and should be considered essential, brands can instead directly access the intent and desire of a consumer as they search for a product or service of interest. If they bid highly enough, they can instantly push them to a landing page or ecommerce experience that allows them to make a purchase – all without taking off their pajamas.

This is powerful, but the specification of this intent – and the proper push to purchase that they require – both arouses privacy concerns among consumers and still leaves ambiguity. While it allows for marketing to consumers on a close-to-one basis, it does not in itself allow consumers to achieve a one-to-one connection with brands, and thus has its own limitations in personalizing offers and recommendations to consumers. What’s more, if ever this platform is significantly constrained or one day simply “goes away”, brands without comprehensive data of their own will be the first ones left in the lurch.

Given that consumers also don’t necessarily search for something unless they feel motivated to, first-party data can also offer the opportunity for brands to promote offerings to consumers that aren’t necessarily looking to buy something. Leveraging the traffic brands get from platforms like Google and funneling them to conversational experiences can tease out more of what consumers are really interested in – even if they don’t know it themselves yet.

 

The Limits of Behavioral Data

Facebook and Google definitely have a variety of data types that advertisers can use to reach out to consumers, but with much of that data being behavioral, it’s important to question whether advertising through these platforms is as relevant to the consumer as is possible today. On top of concerns about privacy and behavior-based data changing what is available to brands, brands need to ask whether the personalization and targeting they use is really as accurate as it could be, compared to the first-party data that they can collect themselves.

Behavioural data is the primary type affected by GDPR, which is likely to be the model for future privacy and anti-trust regulation globally. Source: eMarketer.

Behavioral data is the primary type affected by GDPR, which is likely to be the model for future privacy and anti-trust regulation globally. Source: eMarketer.

Consumers don’t always know what they want or what they’re looking for, but that doesn’t mean that there is truth in the “signals” they send by using these platforms, meaning that there are still cost-inefficiencies present. These can be overcome by adopting an approach of talking to the consumer directly and trusting the general information that they provide. This is what “declarative” data is, in that it is what a consumer “declares” as their interest, need or desire to a brand.

Just the same as behavioral data, however, declarative data has to be generated without triggering the privacy concerns of an individual consumer. This means that the tone, intent and collection of declarative data needs to be friendly, transparent and permission-driven. This kind of information is more deeply personalized than what is currently available, which means it’s more likely to arouse trust issues if not collected conscientiously.

As it turns out, Facebook itself it already pivoting to an approach that is more conversational and one-to-one, taking the approach that brands will more often be directly messaging the consumers of the future. While this does validate the possibilities declarative data can offer brands, it doesn’t get rid of the regulatory concerns that should spur brands to do this on a first-party basis.

 

Where Declarative, First-Party Data Gives Brands New Possibilities

Understanding how declarative data works can be simplified by comparing it to behavioral data, both in how it is generated and what it can be used for. flexMR defines both forms of data as follows:

 

“Actions (Behavioral) – Purchase records, transactional data, search data, app usage

Declarations (Declarative) – Survey responses, vox pops as well as interviews, focus groups.”

 

Brand marketers understand the value of behavioral data, and obviously the expression “actions speak louder than words” can apply with great relevance here. But how many actions will be allowed to speak going forward, and is it possible that such intimate insight could be missing an opportunity to engage and maintain relationships with consumers over the long term, rather than simply up to a first acquisition?

The main criticism of this could be that the forms of declaration listed above are, in fact, cost intensive and biases of their own. Survey responses, interviews and focus groups may speak to what consumers think they want, but not what they actually feel their wants or needs are in moments of product discovery. Netquest also lists measurements like NPS and mobile diaries as declarative data, but is there something both these definitions are missing?

 

How to Bridge the Gap with Conversational AI

That’s where Conversational AI comes in. Conversational AI is a specific application of artificial intelligence, generally found in voice-based systems like Siri, Amazon Alexa and Google Home, but also a solution that brands like L’Oreal and others have gained more traction within the messaging space.

For brands, Conversational AI can be deployed as a sort of automated brand representative across multiple channels, offering guidance, recommendations and instant, personalized responses to consumers as they discover and purchase products and services. This generates declarative, first-party data by engaging consumers in one-to-one conversations at scale. Asking and responding to questions in real-time generates unique data with each interaction, allowing for better guidance and personalized recommendations. The effectiveness of these solutions has begun to take hold in the B2C space, with each interaction generating multiple minutes of engagement, 5+ unique data points and 30% increases in sales conversion on average.

Behavioral data is always a compelling tool for brands, and the advertising platforms that use them – divided at times as they may be – are uniquely suited to allowing brands to connect with consumers at scale. Their limits, and risks to their future, are both becoming concerns however, and in response to that brands should begin to generate and leverage their own declarative first-party data to not only improve the effectiveness of their existing campaigns, but also maintain their performance in the long term.

While past forms of declarative data collection may have been expensive, unreliable or difficult to scale, Conversational AI is uniquely positioned to empower brands to overcome all of these barriers, and experience more success as a result.

Contact Automat to learn more about what first-party data and Conversational AI can do for your brand, or check out this case study on Vichy’s Skincare Expert to see how you can transform multiple elements of your customer experience.