SUMMARY
Mobile Has Been A Powerful Booster To Digital Advertising, But It Is Striding To Turn Another Marketing Chapter
In India, digital marketing, and mobile advertising, in particular, is booming at a rapid rate and has been billed as a prosperous market, supported by many research figures.
One such report is the eMarketer’s 2017 report forecasting double-digit growth for mobile advertising over the next few years. By 2021, mobile will account for just under 62% of digital ad spending’s $2.8 billion as compared to $ 1.73 Bn earlier, a 213% robust growth in 2018’s mobile ad spending of $0.81 Bn.
Driven by accelerating mobile internet penetration, dropping data charges and fast emerging low-cost smartphone, mobile has been a powerful booster to the growth of digital advertising in India. The outlook is promising in the way it is striding to turn another marketing chapter. The revolution now is on the way, moving silently but we still can find this out through certain key signals.
User Profile Still Effectively Enough For Marketing?
Marketing quantitative and qualitative approaches hitting the ceiling
The classical marketing concept emphasises “Audiences Centered”, which is trying to find out your target audiences well for an effective communication. “User (Audience) Profile” is created to paint how your audiences look like. Many marketing plans start with this idea to lead to subsequent strategy and tactic. This is very common and basic element of a Media Plan.
However, a very fundamental question is “how can we know user profile exactly”? This normally refers to either Quantitative Approach supported by ‘Statistics Theory’ such as market survey or Qualitative Approach through in-depth interview or focus-group discussions. In reality, the prevailing case to generate user profile is simply made by key owners in the company of media planner, product marketing manager and marketeer, responsible for this marketing plan.
This so-called user profile, can be only drafted by a common sense or personal observation (or personal imagination) in many marketing plans. While the presentation of user profile still sounds reasonable, do we doubt or question the accuracy of this user profile analysis?
Even this is analysed by a statistic process and the true picture of user profile can still be twisted and its real face can be hidden. Not to mention many critical details like user’s lifestyle and predicted behaviours in different context are difficult to depict precisely with a classical marketing approach.
User Behavior Prediction Matters
From cause-and-effect to real-time outcome oriented
This is because a traditional social science including marketing research relies on statistics rooted in Theoretical Sampling and Scientific Inference, which figures out the co-relation between ‘cause and effect’ in marketing context for knowing how to communicate with target users properly. However, the “Scientific Conclusion” might not be stable and accurate due to uncertainties affected by “unseen (unconscious) or intentional mistakes”.
In addition, linear logic bearing is constrained and it’s not easy to handle the complicated marketing scenario where the faces and minds of users are dynamic and ambiguous given that rational and emotional consumer behaviours. If we merely pursue the “Scientific Logic” behind marketing statistic support, the marketing accuracy can be very unstable.
Regardless of ‘cause and effect’ concept, “Real-Time Outcome” generated by Big-Data AI Technology can be the new nuclear weapon in marketing. When “real-time outcome” is addressed, the logic between ‘cause and effect’ would be not important at all.
Instead, to pursue the “outcome” in real time or at least in a very short time really matters when it comes to marketing competitiveness. One example of the outcome here is “when some signals (like some key words searched or some behaviour symptoms) arise, some outcomes are very likely to happen accordingly. Even without any sense to know the ‘cause and effect’ between “signal and outcome”, this would be not an issue.
As long as we can capture the co-relation between “signal and outcome” fast enough powered by Big-Data and AI technology, this would certainly defeat the typical marketing approach.
Big Data and AI Will Dominate in New Marketing Era
Know your users even better than they know themselves
Notwithstanding the potential of Big-Data and AI, how we leverage them for marketing could be still non-tangible for many advertisers and marketers who might not truly sense their power. Being able to know your users even better than they know themselves — is not a myth but reality that is fast dawning on us.
While IOT is going to be much more mature everywhere in the near future, everything will be connected to the internet for the potential of data collection and data analytics. With huge data feeding, it starts to nurture reliable algorithms to be born and will get us closer to AI capability. As a matter of fact, AI for marketing on user prediction is not going to be a theory anymore.
Nowadays cameras on the street keep growing and very soon many widespread life objects such as street lights, outdoor billboards and outdoor displays (LCD monitors in the malls, elevators and public sites) are also going to be connected to the internet. All of them will be the data collector, not to mention all those personal or family belongings like phone, wearable devices, TV, and refrigerator. Can you imagine all those “contact points” for 24×7 receiving your behavioural data will be silently running forward.
Once all those (offline) data are integrated to your online behavioural stats such as your preferred purchase items and the online browsing pattern, probably, we won’t feel confident to say we know ourselves the best because many of our behaviours are rational and emotional mixed together.
However, Big Data and AI technology can handle it with the ease at the end. Certainly, the things discussed here for data application must be under the protection of de-identification and re-identification of any individual according to law. In a word, for the integration of online and offline data in IOT and AI era, this would completely reverse the existing marketing way.
Data-Driven Intelligence
Your own “User Data Model” shall be a core to digital marketing investment
As a marketer or an advertiser, how to prepare for the challenge in new marketing era since user profile is not sufficient enough to deal with diversified marketing context? One upgraded concept of user profile is to build your own “User (Consumer) Data Model” which is an ongoing refinement process to see through and to further predict your user’s behavior for marketing activities.
This happens by collecting (potential) user’s data from a variety of online and offline data sources to be followed by the deployment of big data technology such as machine learning to filter out less meaningful data and to keep optimising for a reliable algorithm development for the prediction of user’s behavior in certain cases of a scenario.
This user data model is as unique as a tailor-made consideration which only caters to your specific user targeting for maximising your digital marketing investment.
Your target users of different products or services shall be constructed with a correspondingly unique user data model. With such a uniqueness, the targeting could be quite accurate even to reflect the lifestyle of your target users. This is a very data-driven approach to reform your marketing strategy and is also a crucial step leading to the AI Marketing.
In short, User Data Model is the reflection of your profound User Insight rooted with Data Power triggered by Big Data and AI Technology. This unveils a revolution facilitated by Data-Driven Intelligence in reshaping the marketing industrial. One who can sense and ride on this trend with a right marketing transformation will definitely win a great victory.
