Manu PrasadFrom having to ditch one martech tool after half a year and moving to another tool, to eventually end up with a homegrown system, Manu Prasad, chief marketing officer of Scripbox shares his martech journey with ETBrandEquity.
Prasad reminisced about Scott Brinker’s martech blog, which started way back in 2008. “Brinker’s 2011 marketing technology landscape had 150 service providers. In 2022, it has over 9900,” he said, as he pointed out how ‘figuring out’ isn’t the way forward in martech anymore. It all depends on how one ‘figures the way inside it’.
1. What was it like when you came across the concept of martech initially? How did you figure your way out of such an alien concept?
The concept is much older, it’s just that the adoption has probably picked up in the last few years. Scott Brinker started his martech blog in 2008. The lingo has also moved from the OG direct/database marketing to drip marketing to marketing automation, and the thinking and tools have evolved accordingly.
Even in my earliest ecommerce role back in 2011, we used to have a version of this. Back then, the tools were fewer, but email, SMS, retargeting on display channels all existed and some of them could be automated too.
Brinker’s 2011 marketing technology landscape had 150 service providers. In 2022, it has over 9900. That’s a 60 times change in scale and probably a lot more in terms of complexity.
So there really is no “figuring out”, one has to figure the way inside it. A steady process that continues to this day.
2. And how have you, as a marketer, been experimenting with the said process?
In the early days, the processes were quite linear. Based on a lead capture or just a site visit, there would be emails/SMS and pixel-based retargeting respectively on say, Google or Facebook.
The experiments then would be relatively simple – for instance, on the timing of the mails/messages, the subject lines and optimisation of retargeting channels.
But things have changed. The capability of tools have become far more advanced and real time, consumers access the brand across devices and the only tech that doesn’t seem to have kept pace is spam filters. This means that while the older experiments are still reasonably relevant, there are new ones built around multiple segments and their granularity and nuances, with the objective being extreme personalisation.
As they say, a segment of one. From chatbots that assist the customer soon as they are on the app/site to automated workflows for referral and advocacy, the experiments are now across the customer lifecycle.
3. Any instances where the deployment didn’t exactly work out the way you wanted it to?
It happens quite a bit, because the entire ecosystem is going through a steep learning curve.
Additionally, what works in one domain, or even another organisation in the same domain may not work for you. In the early days, I remember having to ditch MailChimp after half a year after some compatibility issues, switching to customer.io which itself had only recently launched and finally ending up with a homegrown system.
In another startup, we started with a basic system of our own, switched to a very respected name in omnichannel customer engagement and just couldn’t make it work for us.
There have been numerous experiences with adtech partners not being able to deliver what is promised. And an instance where, when I was pitching WordPress as the CMS, I faced an uphill struggle because the startup had a malware incident involving a plugin.
The only constant has been trial and error.
4. What kind of martech initiatives has this trial and error led you to take up?
Given the domain we operate in, our usage of readymade tools for our stack is relatively limited. In fact, as privacy and security concerns grow, we are even more careful about the technology we integrate into our stack.
A bunch of our new initiatives therefore are at the very top of the funnel and limited to adtech or social, as opposed to say CRM, data management or even marketing automation.
In the latter set, we either have existing partners, or our own systems which we have built and refined over the years. These also help us deploy first party data far more efficiently and effectively deeper down the funnel.
5. How did you determine which stack would fit the best?
In terms of assessment, the martech stack is a function of the business context it exists in. Not a complete set, but multiple factors from current and potential needs and challenges, and product roadmaps, to budgets, scalability, flexibility, compatibility and impact on customer experience, are part of the process.
6. And what outcomes did you receive from the same?
We have an example at the top of the funnel – using WebEngage for our email marketing automation. We were able to get a lift of 25 per cent in open rates thanks to a bunch of things – optimising send-time, frequency capping and using cohort analysis to implement rule-based automation and thus personalisation.
Another win for us has been what we call a product nudge. This was built inhouse and resides in our product dashboard. This has not only helped our customers discover additional products more easily, but thanks to being data-driven, we are also able to customise and A/B test the proposition and messaging for different segments resulting in higher adoption.
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