‘Cookieless’ Could Still Be A Future Reality

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“Regardless of the cookieless ‘pause’ that we have encountered from Google recently; what we need to understand is that it may still be a reality in the future and this is what we should be prepared for. So the solution is to ensure that you are collecting all the possible first party data points. However simple this may sound, organisations are yet to get their data strategy correct,” says Nikhil Vidhyan, Regional Head of Digital Omnichannel, Ninja Van Group.

Nikhil focuses on crafting customised consumer journeys to meet diverse customer needs across Southeast Asia. His role includes improving Ninja Van’s brand perception, acquiring the right customers, and ensuring retention through integrated CRM systems and effective use of paid and owned media channels.

Despite reduced data availability, there is still an overload of data. Marketers must handle structured, unstructured, and incomplete datasets across multiple platforms. The goal is to integrate this data effectively to create actionable insights and drive better targeting and optimisation. Nikil also discusses app stickiness and reactivation of idle users.

Excerpts from the interview:

• What are the biggest challenges of digital marketers today?

The biggest challenge of digital marketers today is ‘Data’ i.e. collection of data and usage of data.

• Collection of data: All of us are aware of the long pending cookie discussions that have been going on for the last couple of years and regardless of the cookieless future pause that we have heard from Google recently; what we need to understand is that it may still be a reality in the future and this is what we should be prepared for. So the solution still is to ensure that you are collecting all the possible 1st party data points; however simple this may sound, organisations are yet to get their data strategy correct. Hence collection of the right data is going to be extremely important starting with setting a data framework which is future-proofed. To add to this, all the industry-wide privacy conversations will only further limit the data that will be available to capture and hence it is important to have a strategy to collect all possible data points. More data will mean better actionable insights, from where we can go into better digital targeting and optimisations towards precise outcomes.
• Usage of data: Given the various tools and technology that we are surrounded with; there is tons of data that is being generated. Regardless of the reduction of data that we are discussing, there will still be a lot of data to deal with. Then the question is how are we going to deal with all the data and make sense of it. For running successful digital marketing initiatives we need to first deal with all kinds of structured, unstructured and incomplete datasets across multiple tools and platforms and do our best to marry them together thus building end-to-end insights.
• How much should mobile app marketers rely on data analytics and AI to shape their strategies, and what are the potential pitfalls? 

First things first, data will continue to be an important commodity for mobile app marketers. The question is how much data will be accessible in the future. We did touch on the subject of privacy, which is linked to this question, so I will elaborate further here.

Unfortunately, we have to live with the reality of lesser data in the future due to privacy concerns which simply means 2 steps need to be implemented – First is data collection and second is data modelling.

As we have discussed data collection earlier, I am going to focus on the data modelling part here.

• AI can be your best friend for both collection and modelling but is heavily skewed towards modelling using the limited data that will be accessible.
• Given that we are working with limited datasets, AI can be the solution to help stitch the data story so that we can derive actionable insights.
• AI solutions could be in the form of modelled conversions where limited data signals are used for better targeting and optimisation.
• We can also use AI for building efficient hybrid attribution systems which will work better as we are living in a multitouch world.

Potential pitfalls are trying to get it right the first time and then applying it to your digital marketing strategy – you will never get it right the first time due to the required iterative nature and it has to be a test-and-learn approach. Do not waste too much time to get a perfect outcome. Focus on collecting as much data as possible to let the system learn and provide a better outcome.

• What does it take to make an app experience sticky?

A sneak peek of the iOS app store or Google Play Store shows us the clutter that we are dealing with. There are tons of available apps doing similar things and hence the question is how do you differentiate your app?

This is where app experience becomes extremely important, leading to customer delight. Once you acquire customers, it starts with building a consumer journey that intuitively answers the customer’s pain point without much fuss and communicates the value proposition in the process.

Key principles for this include:

• We should have a design that is user-centric so that we do not give them reasons to close the app or uninstall it.
• The app should provide a seamless user experience so that it is easy to use and navigate. Do not give them reasons to get annoyed or feel lost.
• Build personalisation at scale so that every experience is tailor-made and not generic. Given the amount of data being collected, it should be easy to provide personalisation. We all understand the need for customised content, which could be in the form of rebates, promotions, gamification of compelling content, etc.

Building a successful app is not easy and requires a lot of testing and learning from those experiences. So, some of the defaults in this process should be continuous learning through user feedback and behaviour data that is being collected. This should lead to app updates for consumer journey improvements.

• How can app marketers reactivate idle users?

At times we are too busy acquiring new customers that we forget about our existing customers who may potentially churn. So it is imperative to identify customers who may potentially churn and take the necessary actions before they completely leave. This will always be easier than reactivating customers who already churned. To identify which customers may churn, we may need to look at the behaviour of users on the app much more closely along with the transactional behaviour. All app marketers should put effort into reactivating idle customers:

• Segmentation: Not all customers are equal and they should be bucketed based on the behavior that they have demonstrated. Segmentation is the first step so that we can have different communication for various segments. For example, you may want to communicate differently to a customer who has gone idle as of last week in comparison to somebody who has been idle for more than 30 days.
• Personalisation: Once the segmentation is in place, it should lead to personalised communication, which will increase the chances of conversion, which is getting these users activated.
• Medium of communication: We should understand the preferences of the customer and engage with them accordingly. If Customer A has shown more engagement over in-app messages over emails then all communication should be centred around in-app messages.

Offers for idle customers so that they can be enticed to perform the desired action

Implement automated notifications based on behaviour on the app to build more engagement; for example, if a user has items in the cart or a favourite item is back in stock then there should be notifications to drive engagement within the app ecosystem. Feedback from idle customers may show potential reasons why they are idle and we can change things accordingly