Every media buyer knows that data is the key to a successful campaign; the more you know about your audience, the more you can speak to them in ways that resonate.
But every buyer also knows not all data is created equally, and that deploying sub-par data can lead to disappointing campaign results. Data quality, therefore, is paramount to campaign performance.
All too often, however, data quality is a bit of a blackbox. Marketers have little insight into how data segments are created, when they were created, and how often they’re refreshed. As a result, marketers and media buyers may purchase audiences of consumers who have already purchased or were mislabeled.
These are difficult and stubborn challenges that have plagued media buyers and marketers since the dawn of digital advertising. Fortunately, real-time data addresses these challenges head on. A relatively new class of purchasable data, real-time data allows marketers to target consumers at the most opportune time, deliver a more relevant experience to the consumer, drive efficiency in their media spend, and deliver tangible business outcomes.
What is Real-Time Data?
Real-time data, by definition, is based on real signals consumers generate as they go about their digital lives. It’s composed of the shares, likes, comments, searches, clicks and page views observed across the web as they occur.
Real-time data differs from pre-packaged data in that it’s deterministic, not proxied. If I share the video trailer for a new movie on social media, it’s a clear indication that I have an interest in it. Real-time data makes that determination based on my personal actions, and not because I look like other consumers who are likely to see that movie.
This is different from probabilistic or proxied data. Proxied data makes assumptions about consumers based on past actions; if a user visits a baby site, she must be a new mom. The biggest challenge with proxied data? It can’t tell the difference between a new mom and an uncle who’s buying a gift for his new niece. It can be a rather blunt instrument.
The other challenge is that it doesn’t consider the consumer’s mindset. True, a new-mom will be keenly interested in baby gear, but she may also be interested in acquiring a new weedwacker or snow tires for her car. Context — the here and now of an internet session — is a powerful indicator of interest and intent, but it’s largely lost with prepackaged data that’s based on old signals, and sold to a marketer well after the action actually occurred.
This is why the freshness of real-time data is so game changing. It can dramatically improve results in specific applications many media buyers and marketers face. For instance, some sales cycles are short, with the awareness, consideration and purchasing phases condensed to a matter of hours. Targeting consumers based on real-time data in such circumstances is key to driving media efficiency, as there’s no point in targeting a consumer who has already converted.
But real-time data also drives efficiency in longer sales cycles because it sends real and measurable signals that a consumer has progressed through critical phases of the purchasing journey, enabling marketers to act ASAP.
Real-time data also has a high degree of accuracy — either consumers shared this content or they did not, they either landed on this product details page or accessed this product configurator or not. This too is game-changing in that these real-time signals can be fed into advertising and mar-tech platforms to automate smart, data-driven strategies, including campaign optimization and one-to-one personalization.
Let’s see it in action.
Segment Consumers into States of Your Sales Funnel
Real-time data is extremely useful in understanding where consumers are in the purchasing journey and assessing the kind of information that will be most useful and relevant to them at that moment.
For instance, consumers who plan to purchase a new car within the next 12 months are likely to begin the process by visiting car review sites — a real-time behavior that will tell an auto brand these consumers are in the awareness phase. As an auto brand, you’ll want to create a segment of these users, and send them messages about the safety, fuel efficiencies or other benefits that are unique to your brand.
Next, they may visit individual auto-brand sites to read about models and configure a car to get a sense of the end cost — clear behavioral signals that they’re in the consideration phase. You can segment these users and target them with a new set of messaging, such as your financing options or model availability.
Once these consumers search for a local dealer or schedule a test drive, you’ll know they’re getting closer to making a purchase. This is an opportune time to target them with a local dealer incentive.
Map Engagement Behavior and Page Content to Interest and Intent
High quality real-time data, combined with advanced data science and machine learning, allows data scientists and data collection platforms to organize and categorize behavioral signals into taxonomies of meaning. From there, media buyers and marketers can segment audiences based on interest and intent. For instance, a Home & Bedding brand can segment audiences based on interest (outdoor furniture) or goals (renovating a kitchen).
You can then activate these segments at scale in a variety of initiatives, from targeting consumers with a message that speaks to their interests in social media, to customizing their experiences when they visit their web page, or prompting them to sign up for a loyalty program.
If a consumer shares a photo of an awesome patio from Houzz.com, it’s a pretty good signal that she’s looking to upgrade her outdoor space. This is a perfect opportunity for a Home & Garden brand to target her with an ad for its new line of outdoor rugs.
Deploy Smart Strategies Over a Lifetime
Because the data is real-time, marketers can trace the evolution of their audience’s interests, and seamlessly move them into a new purchasing segment. For instance, consumers may discover a brand when looking for an outdoor dining table to purchase. Later on, those consumers may be getting ready to undertake a home or garden renovation project, and in the process, generating important signals to the brand. Knowing what your customers are doing in the digital universe will help you send them messages and offers that are relevant to the projects most top-of-mind.
Real-time data — actual actions taken as consumers go about their digital lives — will also inform your product development roadmap. Real-time clicks and shares will help you understand when long-term customers are exploring other brands, and why, and provide you with the data you need to identify and fill gaps in your product line.
Real-Time Data Belongs in Every Media Buyer’s Toolkit
Identifying potential customers will always be a challenge, but it’s possible to leverage accurate, relevant, real-time data to streamline the process as much as possible. It can complement a brand’s first-party data to drive media even efficiency and better business outcomes.
Here’s why: potential customers are searching the web, sharing relevant content, and engaging with possible solutions to their problems. You can meet them at the right time with real-time data. It’s why real-time should be a part of every media buyer’s and marketer’s toolkit.