How Crucial Is Big-data Analytics In Mobile Advertising?
By segmenting the data using powerful analytics tools, you can break down your audience into different buckets
Photo Credit : ACG Silicon Valley
We're in an algorithmic world. Everything we do on digital is recorded and now, being understood. By mapping a consumer's digital footprint, marketers are able to understand their audience better and run targeted advertising. In essence, we are data. Bits and portions of us tell us a lot about who we are. And yes, there are privacy concerns, and yes, there are major areas that require regulatory control. For this, there's a lot of authored articles out there and I'm not going to attempt talking about one. As a digital advertising man, my area of expertise is to understand how data can make advertising better. How data can help marketers sell their products, bring in more accountability to the opaque world of digital advertising and so on.
From the era of TV advertising to now, data is a clear differentiator in how advertising has changed. There's a lot more accountability in advertising now. The good old days of 'TRP ratings' are obsolete and we're already witnessing early days of mobile and desktop advertising budgets taking over TV ad spends - more so in mature markets. Digital advertising is the future and the role of big-data analytics in advertising is an interesting space. I pick mobile because it's far rampant than desktop advertising and a lot more personal. Maturing markets like India and Indonesia have catapulted desktop advertising because users' access to the internet is via a mobile device and not desktop.
In an environment like mobile, personalized campaigns and hyper-targeted messages play a vital role. It offers a lot more opportunities for marketers to sell. It is the ability of data - in combination with thoughtful analytics around segment, intent, desire, and more that provides value to brands. For data to be meaningful to decide your strategy, it needs to be captured and stored efficiently. Then someone must manage the data, analyse it, and extract value from it. Data, big or not, doesn't add up to anything worthwhile if it cannot be mined to show predictions, results. That is where Big Data Analytics plays a crucial role in the collection, storage and deciphering data to meet the marketing goals.
We have observed that data on mobile has been far more comprehensive than on desktop. For example, we ran a campaign for a leading e-commerce provider that wanted to boost sales for their gadgets category. We ran a campaign for both mobile and desktop and the results were unsurprisingly in favour of mobile. We had nearly 90,00,000 impressions (ad views) a day and got 20,000 conversions on mobile while we received only 5,000 conversions on desktop. While one could argue this was an isolated incident, our network tells us that mobile ads are far more promising for conversions than desktop advertising.
When the real estate for advertising is squeezed into is a 5-inch screen, the ad elicits a lot more response than a desktop - simply because the probability of the user observing the ad increases. This makes mobile a lucrative area for marketers to look into. Comparatively, the outcome of impressions captured on mobile is easier to predict with its nature of anytime, anywhere impressions recorded by users such as frequent travellers, recent travel booking for cold places, visiting online jacket stores, etc.
By segmenting the data using powerful analytics tools, you can break down your audience into different buckets. Will XYZ, male, 20-24, traveller, online shopper, avid sports reader be more likely to buy a pair of trekking shoes? By deriving this insight through analytics, I am more likely to 'convert' a user to buy the product - making the marketer that spends their ad dollars with me, a lot happier. When our business model is built around these conversions, my data needs to be robust. I need to look at technology and ensure that I have enough conversions any given day. By bringing in this accountability, digital advertising is changing. It's more accountable. It's more transparent. Above all, it's setting a standard for what good ad tech needs to look like.
For any business now, while mobile is the centre stage of a digital strategy, big data pushes the benefits of mobile advertising with more personalized, hyper-local and real-time marketing approaches. Which brings me to the big question - do I define a company that works on this technology as a big data one, or an advertising one? For me, every ad tech company is first a data-driven company and advertising happens to support a company that's able to mine this data.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.