According to Chinese astrological tradition, the sign of the monkey is supposed to be intelligent, quick-witted, clever, ambitious and adventurous. In my experience of driving digital transformation across organizations in Southeast Asia, I increasingly feel that the region is similar in persona to a monkey in the Chinese zodiac. If you’re a close observer of this region, Southeast Asia has very much been mobile and mobile app first, thus partially conquering the challenge of monetizing one of the largest social populations of quick adopters with the lowest ARPU (average revenue per user). Nonetheless, data and being smart about using data will still go a long way in being able to resolve problems and continuing to conquer the challenges posed by this unique market.
Before I look into the crystal ball and start suggesting you should be intelligent, clever and adventurous as an ace digital marketer in 2016, I want to draw your attention to certain key trends that we saw in 2015.
1. Tag Management Finally Got Its Due
Organizations finally started to get their data layers and their data layer strategy in place. If you are late to the game and want a head start, refer to my previous article which talks through the why and what of tag management. It’s still relevant, though one big change that has happened in the tag management industry is how tag management is now not a core business model for anyone. It’s a data war where every tag management system wants to be the central data hub, or provide attribution, or even be a seller or buyer of data. Be careful in evaluating what tags you are putting on your site and what data they are capturing, and where that data is being used and how. My favorite story of 2015 is when I asked the Chief Digital Officer (CDO) of an airline in South East Asia how many tags he had on his site and he said 5, only to be shocked when I showed him 28 tags firing off his homepage (thanks Ghostery). Resources exist for tagging up, but no one has money to remove tags. Massive digital nightmare, and a potential privacy/legal issue.
2. Testing the waters with testing
With a solid analytics foundation, any business that wants to impact ROI needs to get started with testing. While testing is nothing new, Southeast Asia finally saw its e-tailers and banks getting started with simple test strategies, mostly focused on re-targeting segments. Even telecom companies are waking up to the massive data sets they are sitting on, with little or no value being realized right now. With innovation in tech and easy-to-use front end test set ups now available, the biggest hurdle to getting started in testing is actually a people issue and not a tool issue. Organizations fail to realize that for a successful test strategy, you need to include user experience, product, marketing and analysts, with a clear owner. My argument has always been where analytics costs you money, testing and targeting makes you money. And if that is the strategy you adopt, you should be able to get the teams to contribute. Having testing KPI’s tied as soft KPI’s to individual performances usually serves as a great accelerator to get started.
AB Test>Multivariate Tests>Rules-Based Targeting>Testing Analytics powered Segments>Automated Algorithmic Testing – usually forms a basic framework you can get started with and realize value over time.
3. Data management platforms – what are they?
I spent quite a bit of time evangelizing data management platforms last year, and while it’s not a new technology trend globally, it was the hot new tech in 2015 in marketing technology across South East Asia. Mobile programmatic also emerged in 2015 and agencies moved ad spends to mobile, now that programmatically more mobile inventory was available. With data sellers arriving in a big way from Eyeota and Axciom to ADARA, marketers woke up to the value of their data, and now wanted a data management platform to be able to leverage the value of their first-party data and activate audiences across the programmatic landscape.
While third-party data is great, it offers no competitive advantage, and the big trend within data management platforms was second-party data or data co-op between advertisers and publishers, or just advertisers.
Merging cross device data and building a device graph were big reasons I heard from users wanting a data management platform. The most interesting argument I heard was from a mobile programmatic vendor, who was offering probabilistic match data as a free add-on to convince potential advertisers to move ad spend to mobile.
4. Attribution was everywhere, although more as a buzzword
Continuing from 2014, attribution was a need rather than a nice-to-have in 2015. But the predominant business case for attribution was budget approvals, as turf wars between display, social and search teams continued, rather than mid campaign optimization. In 2016 smart marketers will use attribution they now have in place to make mid campaign tactical changes rather than a quarterly or six monthly review of ad spends by channel and campaign.
Another important thing to understand is that attribution is not media mix modelling and currently attribution is seen as a way to build media plans, which is not the ultimate use case for it. A simple way to think about this is – media mix modelling involves analyzing more factors including financial, seasonal, demographic, among others, to plan for media spend and to look into the future, whereas attribution looks back at campaign spend to make tactical changes to the campaign spread to improve ROI.
5. Big data versus smart data
Big data as a buzzword died slowly as people understood the word better, and realized it was nothing new. Customers started questioning volume, velocity, variety and veracity and the need to invest millions of dollars in hardware and software waiting for the ROI, and started looking at analytics as a service to help solve business problems. The need expressed was smart data rather than big data as business wants questions answered and problems solved rather than training academicians and statisticians to store, refine and analyze data. Rather than determining models and data cleansing, customers want cloud technology to apply the right models at the right stage and solve business challenges for them. Start thinking about what you want to do with data in solving business problems rather than just collecting it.
6. Tag that App
Continuing the trend we saw when mobile surged ahead of desktop use in South East Asia, business started to realize the value of investing in analytics on apps to look for insights beyond the basic health metrics of launches, crashes, operating systems and devices. Now,we’re looking at usage, cohort analysis, geo location, testing and even targeting. The Make>Measure>Monetize>Optimize cycle got applied to mobile apps, and the next stage here is cross device deterministic match for logged in users, and figuring out a probabilistic match for non logged in users to understand usage behavior across channels, and then being in a position to optimize the user behavior across both channels. Attribution was a key challenge where marketers want to invest in mobile, but have a hard time communicating the value of mobile in today’s complex cross channel journeys.
7. Testing deployments
There is an old tech adage of GIGO (garbage in garbage out) and it applies well to analytics deployments. A leading retailer had product views being fired on every product recommendation as well, which was skewing data and leading to an incorrect count of product popularity. Imagine the impact of that on recommendations, inventory management and algorithms chewing out incorrect predictions. Test every analytics deployment, and test every deployment even if analytics wasn’t altered. Integrate analytics testing into application testing. Validation of tags as a process is important, and sometimes critical.
Digital marketing maturity is arriving right now in Southeast Asia, and as I learnt last year, there are pockets of innovation that are making some marketers leave the other struggling in their wake. As I said to a visitor from the US who was generalizing Southeast Asia as not a very mature market – its not the maturity of the markets but the maturity of the marketers that is important.