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Tech in check: Havaianas’ SG and MY MD Jaime Syjuco

With over 20 years of experience in both digital and traditional commerce, Jaime Syjuco (pictured), currently managing director of Havaianas Singapore and Malaysia, experienced first hand the upheaval of traditional retail brands and branding agencies and disruption by eCommerce and digital marketing.

For the past three years, he has founded two startups focused on transitioning traditional commerce into the digital era: Lean Retail Labs, a consultancy to digitise retailers, and Aroodai, a startup developing AI for the retail industry. He had previously held strategy manager roles with Accenture and eBay working in the Silicon Valley.

In this edition of Tech in check, Syjuco gets real with his struggles and views on how retail brands and their digital agencies can survive the current retail apocalypse.

Marketing: What was your first digital role like?

I’m lucky that my career started “backwards”. I started first in digital, thereafter moved to brick-and-mortar. My first digital roles were as CRM strategy manager for Accenture, then e-commerce strategy manager for eBay. After that, I moved to Asia to build a brick-and-mortar retail business for Havaianas and other brands. I’m now leaving again to focus on merging the best of both worlds: “digitalising” brick-and-mortar.

My first digital roles were always hinged upon direct attribution: I needed to attribute activities and spend in digital with results in the real world. My roles as strategy manager were always about collecting data, laying a “digitalising” road-map for clients, implementing it, then making sure that the client’s investment dollars and efforts in digitalising showed direct attribution to the right business metrics.

Marketing: What was your biggest tech blunder?

My biggest tech blunder was recently with my brick-and-mortar stores. Being the data-geek that I am, starting in 2010 I started “digitalising” my brick-and-mortar retail stores by  installing as many available data sensors and systems possible throughout, making my stores the “most wired” high-tech stores in Asia.

But although I was accumulating data early, I didn’t start using all the data until more recently in 2015 when the retail apocalypse started. It was too late to save the whole business.

So far I’ve only been able to save 25% of my business from digital disruption.

My wake up call was in 2015 when P&G dropped that bombshell and announced that it had cut the number of their agencies by 40% globally, essentially because of their agencies’ general inability to prove marketing attribution.

To be fair, up until 2014, the offline retail and brand business in Asia was just “soooo” easy to make money in, it was a goldmine. Anything I did worked. It was a growth environment: new malls were expanding and supplying more square-footage, department stores were still a relevant venue, new entrant brands from Europe, US and Japan had space to expand into, fast fashion hit scale, marketing budgets were extravagant, and consumers finally had easy access to a plethora of new affordable on-trend products and brands previously unheard of.

During that retail heyday, I was able to quickly open brick-and-mortar stores to saturation, expand into hundreds and hundreds of wholesale doors, carried 95 different fashion and lifestyle brands, and accumulated millions of social network Facebook friends/likes and engagements. Large profits meant I had a large marketing budget and could afford Triple-A marketing agencies.

That previous smooth business growth environment distracted me from sticking to my core digital DNA: I should have continued using data to attribute my resources to long term business viability and competitiveness (and in my case: survival). Then the global retail apocalypse hit in 2015, and now the whole industry and their digital agencies are in the throes of immense disruption.

Marketing: How did you overcome it and what did you learn from it?

We almost lost 100% of our whole business by not watching the data. I wouldn’t say we have overcome it, but we have managed to save 25% of the business and still remain viable and profitable.

Starting in 2015, we started looking at the data carefully and found alarming declines: mall visitors, conversion, retail price levels, and basket sizes. Marketing attribution, consumer responsiveness, and store engagement levels were also trending downwards. Conversely, we found online competitors gaining market share, their pricing becoming more competitive, and their merchandising and assortment widening.

The biggest learning our analysis showed was that a whole set of 16 new paths-to-purchase had emerged from the digital disruption, and no one in the industry was measuring these yet. By spending these last three years with laser-focus on measuring attribution across all paths-to-purchase, we embarked on a rapid-fire approach of measuring and micro-testing many new cross-channel campaigns and proof-of-concepts, and found promising new technologies and channels that customers were responding positively to, such as mobile, chat, offline-to-online, online-to-online returns, and eMarketplaces.

The learnings from this experience are clear:

  1. Start Early: We should have started measuring our attribution earlier. If we did, we could have reacted earlier and avoided much of our downsizing and store closures.
  2. Start rapid testing of new technologies and micro-marketing campaigns to identify the opportunities and laggards. The 16 new paths-to-purchase are proving to be urgent and critical to our survival. Showrooming, Webrooming, Offline-to-Online shopping, Online-to-Offline returns, Mobile and Chat are the new survival tools for the industry.
  3. We had to hack together a Cross-Channel Micro-Dashboard to give us daily monitoring of all our metrics and online competitors pricing, campaigns, merchandise and assortment, so we could react quickly and stay competitive.
  4. Our regular marketing teams and previous agencies were not able to embrace and execute this new “real-time” data-driven micro-testing philosophy. We had to create a new external “digital innovation” team to make this all happen.
  5. Convert our Ion Orchard store into an “innovation test lab” for rapid and low-cost testing and data gathering.

Marketing: What are some of the common challenges you face with digital today?

Having a limited mindset of measuring only the attribution between the one overlap between offline and online, which the industry calls “omnichannel”, is the biggest challenge the industry faces. The 16 additional channels we discovered are uncharted territory, and we need to evolve quickly to address this threat as an opportunity.

For example, we found that 30% of our store visitors are “showroomers”, they visit our stores to try our products, but then buy online – some at our own sites, but others at competitor sites. This creates three new separate distinct sub-channels that need to be addressed. By applying this same analytical approach on click-&-collect, offline-to-online, online-to-offline, returns, webrooming, cross-channel members, mobile, chat, digital-marketing consuming – you get the picture. These create multiple sub-channels.

We have the challenging task of measuring and monitoring these, running new campaigns, then addressing the relevant ones.

Another challenge is finding marketing agencies that have brick-and-mortar domain expertise. To understand which Offline-to-Online campaigns to run needs deep understanding of how brick-and-mortar brands deal with the cost and investment of physical assets such as store leases, stock turnover, staff performance, merchandise assortment, product lead times- all of these are part of the financial equation that drive marketing budgets that digital agencies don’t understand.

The final challenge is that brand owners and agencies are still largely afraid to shed. Digital disruption of our industry requires us to disrupt ourselves, our own internal structures, size and costs of our brand’s and agencies’ organisations, and we will have to shed stores, sales and people in order to make the necessary changes to survive.

Marketing: Are there any digital trends which excite you or that you are wary of?

The most exciting digital trend by far-and-above everything else is combining brick-and-mortar data with real time AI, essentially how Amazon sees the future.

Real time AI is now accessible and affordable, and can power almost everything for brick-and-mortar brands with predictions, recommendations and content, similar to how it is done in eCommerce. As a retailer, I am constantly bombarded by vendors and agencies selling me intelligent mirrors, chatbots, mobile apps, merchandising automation, programmatic advertising. But none of these can work effectively without my own data plus real time AI.

Take Amazon and Google for example. They both use data and AI to decide what product, price, bundle and content to recommend to you as needed. As retailers, we need the same approach with AI to know what to offer our online and brick-and-mortar customers (and the cross-channel customers too) in real time. AI now achieves this effectively and affordably.

For that matter, all the other exciting digital trends such as VR, Chat, QR code shopping and payments will need data and real time AI to make them work effectively. Everything starts from AI.

Conversely which digital trends I am most wary of? That would be Amazon’s capability to use Data and AI to create extremely effective product, content and sales recommendations for customers, much more accurately than I can offer my own customers. For example, I’ve just learned that Amazon collects 250 data attributes of each of their products, while I only keep about 10 data attributes for each of my products I post for sale online. This means that my AI only has 10 data points to generate a recommendation to a customer…while Amazon has 240 more.

Marketing: Any top tips for marketers and brands embracing digital?

My top tip would be to start using your data now and build you’re AI algorithms today, even in a small way. Contrary to popular belief, you do not need big data for retail applications. Just a couple of years’ data will do. In some cases even just a few months. But you still need at least six months to one year of time for algorithm development, and if you don’t start now, you wont be able to make all the new fancy retail tech tools work.

For example two years ago we started an affordable project to develop an AI to do our monthly stock purchases, and today it is already surpassing our human buyer’s ability to predict stock requirements. Another affordable project we started just this year was to empower our store managers and marketers with AI driven in-store recommendations and hyper-local online ads, which is already exceeding our human  team’s ability to make correct recommendations.

Lastly, create a cheap-and-quick way to daily track and analyse your data and analyse attribution and path-to-purchase. Assemble a useable omnichannel dashboard. Brick-and-mortar brand retailers don’t realise how much data they have, and how straightforward it can be to analyse attribution and path-to-purchase. You need this now, and you don’t need a fancy and expensive BI software, just hack it together. That’s what eCommerce companies do, so should we.

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