Intent Marketing: An introduction and it’s advantages over Traditional Audience Marketing

The current Marketing model followed by most Agencies relies heavily on Audience, Demographic and Interest data. They are extremely useful in helping us understand who our audience is and what they are generally interested in. However, they fall short in answering the obscure question of what they want to buy? Ironically, this is the end goal of all Agencies, we are all here to sell something – from products to ideas.

Let us take the example of a 42 year old sports enthusiast. He’s very active in outdoor sports but has a particular interest towards Cricket. Additionally, he is in a high income group which allows him to afford the premium range of Health Foods. But he does enjoy an occasional cheat meal of Chocolate pastries.

The challenge with our user here, is that he simultaneously falls in multiple Demographic and Interest categories. However, none of them can predict the exact or even approximate timeline where he’d want to switch his dietary or sports equipment needs. Which translates to him seeing ads for Gym equipment when he may be looking to purchase a new Bat. Or seeing an ad for a new chain of Organic food restaurants (at a discounted price) when he is really craving for that Chocolate cake.

This is where User intent marketing comes in, by carefully analysing his search patterns and juxtapositioning it with his Interest, Behavioral, 1st and 3rd Party audience lists, we can make relatively accurate predictions of his purchase intent in the near future.

This is because users generally tend to invest a lot of time in Web and YouTube search before making purchases that carry financial or emotional significance. It makes them temporarily jump between Audience buckets which can be pinpointed by using User Intent marketing techniques.

User Intent Marketing usually entails the following:

Demand Synchronisation: this is a Synchronisation overlay that we are able to use via search trends for a set of keywords, and which will allow our delivery to be triggered dynamically in real time in line with interest. Using this strategy would allow us to time our ads in line with when there is the highest interest, thereby increasing our engagement.

Optimising User Engagement: Data can provide useful insights into who your customers are and their interests. This helps marketers analyse their customers’ engagement towards a particular brand and their interaction with the web.

Improving Search Marketing: Isolating keywords that are most effective, while helping the Sales funnel, also helps small businesses identify and highlight the keywords that are responsible for purchases.

Time Lag Insight: Using past information around typical consideration times for certain verticals to determine when, and at what frequency, ads should be shown for maximum impact. If a user is browsing for a pizza the window to convert is very short and the best time to serve an ad is right now, conversely, if they’re browsing for a holiday then ads need to be staggered over a longer period reflecting the nature of larger purchase decisioning.

Making use of DMPs: Checking the history of interest that a user has with a Product helps while sending them personalised offers.

API Syncs: Away from the computer there are myriad other real world phenomena which can influence user intent. Umbrella sales increase when it rains, investments move with financial market prices, generator sales may peak following a power outage. Whether it’s cricket scores, train times, what’s trending on Twitter or anything… really, if there’s an API available these can be used to trigger ad delivery to reach user at the most optimal time.

Finally, understanding your customer is the first step in optimising your Intent Marketing funnel. In order to generate useful leads and push purchases, you need to understand when your customer is in the market, looking for something that only you can provide.

About the author:

Haliga Uday Kumar, Programmatic Senior Trader, INDIA & SAARC, MiQ Digital India