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Tresl Analytics Makes Scaling Up for E-commerce Shops Easy With Auto-generated Marketing Insights

Aimee Wu 2021/06/01
 侯俊偉攝影
侯俊偉攝影

John Chao, former Linkedin senior manager of data science, found that ecommerce brand owners are having trouble turning customer data into gold, even worse, some of them don't even recognize its practical use. With Tresl's automated marketing tools, Shopify online retailers can expect to see the magic of the Midas touch, interpreting customer data into revenue.

Unable to visit brick-and-mortar stores owing to social distancing orders, consumers are proactively taking up the new habit of online shopping. According to a trend report by BigCommerce, while 14.1% of global retail sales were e-commerce purchases, the percentage is likely to see a lift in the days to come, amounting to 22% by 2023.

The implications for e-commerce brands include shifting customer journey, greater emphasis on consumer experience, and a better grasp of website traffic management. In order to orchestrate a marketing strategy that recenters around these new trends, e-commerce brand owners must leverage data effectively.

"What e-commerce brands are struggling with is they do not possess the proper knowledge to analyze customer data, interpret customer behavior and lay out marketing plans accordingly," says John Chao, co-founder and CEO of Tresl.

Equipped with strong data science expertise when working at LinkedIn

John Chao spent a large part of his childhood in Taiwan, later immigrated to Canada, and pursued a master's degree in statistics at Stanford University. Studying in the bay area sharpened his instincts to do things from scratch. "Starting your own business is all the rage at Stanford. Particularly with Mark Zuckerberg's Facebook trend at that time," John reminisces.

Prior to starting his own company, John Chao worked at DemandTec Solutions (later acquired by IBM) as the sales modeling manager, working closely with top players in the FMCG industry such as Walmart and Target. John has also worked with marketing agency WCG, helping clients in the entertainment industry, including Warner Bros and Sony Pictures, make box office predictions.

John found that there was a gap between how his colleagues perceive data, and the way they should be used. It was also the time when DJ Patil, former data science lead at Linkedin, coined the idea of the newest sexy job "Data Scientist". John said, "Data scientists have similar qualities to statisticians, but I think data scientists are more capable to solve problems that marketers are facing, as they have a broader perspective, and resort to more complex approaches like machine learning."

Later, John was recruited by Linkedin as their data scientist. With his data analytics expertise, he developed a B2B sales prediction model that helps discern which companies should be targeted as Linkedin's clients, giving each company a score based on existing data. "What I learned at Linkedin is that business analytics means data science with a practical business need in mind," concludes John.

John worked at Linkedin as a leading data scientist for 3 years.

Identifying the problem: Making data science accessible to all sizes of companies

Having worked with several major companies in the entertainment, consumer goods, and social media industry, John pondered the possibility of making "data scientist" accessible to broader companies, and not just a niche for already giant corporations.

"For e-commerce brands, one of the biggest obstacles that stand before scaling up is not having resources and capabilities to hire a data scientist," says John Chao. Data scientists are experts with sufficient coding skills, data analyzing insights and business acumen. The million dollar question is, therefore, how can smaller brands also get hold of their business data.

Curious and eager to float the idea of data science into practical business needs, John got an inspiration at a gathering with Stanford alumni. Why not use ready-made customer data on e-commerce platforms? This idea of building micro apps on existing websites struck a chord with John, as it provides the data, app ecosystem in one platform. Tresl can pick up from there, and develop a data analytical tool for users.

Micro apps allow users to get in, interact, and get out of a service with much ease. Think of the weather widget on your smartphone, which allows you to look at temperatures, chance of rain, and weather forecast all at a glance. Building data analytical tools with micro apps is exactly like this. For the service provider Tresl, it can extract data ready-made on the platform, while for the e-commerce brand owners, they get access to data science service just by downloading the micro app, a piece of cake.

Allowing e-commerce brands to thrive with data science

Offering data analytics through Shopify, the fastest growing e-commerce platform

John and his team developed Segments, an app on Shopify that aims to help e-commerce brands access data analytical tools. It is an advanced customer analytics platform to help you easily sort, segment, and target your customers based on order history and purchase behaviors.

The e-commerce software application platform Shopify on which Segments runs is Ottawa-based, with more than 1.1 million shops that generate roughly 8.6% revenue with regards to the e-commerce industry. Shopify offers online retailers a suite of services including payments, marketing, shipping and customer engagement tools. The market is still growing, especially under the pandemic, growth numbers are seeing three digits.

Leveraging commerce data through application programming interface (API), Shopify has articulated an ecosystem similar to that of an app store, allowing the so-called "Shopify partners" to offer database services to online retailers.

Tresl offers charts that clearly show the trend of orders placed.

Know your customers like a confidant through data analytics

With Tresl, brand-owners on Shopify can roll out precision marketing. For a makeup brand, there could be different replenishment dates for different products - It might take up to 3 months before a customer runs out of mascara, while just 1 month for sunscreen. By getting hold of the "product life cycle" of each item, retailers could understand when to send promotion deals to customers.

Tresl allows precision marketing, that is, distributing promotion deals to the right person at the perfect timing. What's better, it could be done automatically. Cross-marketing-channel integration allows brand-owners to send out promotion emails via the Tresl platform. Without much additional cost, the ineffective demographic-based customer segmentation approach becomes obsolete.

"Brand-owners should know which items are frequently bought together such that customer lifetime value shall be maximized," John says. With Tresl's "product combo" function, a report analysis on which items should be promoted together is delivered to brand-owners, helping them make marketing decisions.

With Tresl, online retailers can obtain data insights to marketing questions such as what product combo works best together, which channel is most lucrative.

John highlights the competitive advantage of Tresl as "being human". Tresl offers direct marketing insights to its clients. With its enterprise plan, data scientists from Tresl's team will offer tailored strategic insights to companies who wish to deeply explore their data. It would be like having your own team of data scientists.

Tresl's 3-tier pricing plan is "small business", "growth", and "enterprise". Currently about 10% of its subscribers are charged users. Tresl's service is exclusive to Shopify users, which is seeing a staggering revenue increase of 101% year-on-year in 2021.

About the Author
Aimee Wu
Contributor
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Aimee Wu is a journalist and business news translator with a keen interest in sharing innovative technologies developed by Taiwan-based companies. She is pursuing a master’s degree in translation and interpretation at National Taiwan University.

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