About Tencent Africa

Tencent Africa is dedicated to making every day easier for customers and brands. Opening its doors in 2013 as WeChat Africa, the company is responsible for WeChat operations on the continent.

Industries: Technology

Location: South Africa

About Siatik Systems

Founded in 2008, South Africa-based Siatik Systems is a leading Google Cloud Platform solutions provider with a focus on cloud integration services, information technology consulting services, and bespoke software engineering solutions.

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As one of Africa’s leading technology companies, Tencent Africa is responsible for WeChat operations on the continent. WeChat Africa has successfully launched a number of features including the WeChat Wallet, a mobile payment service for smartphones, which enables seamless and secure transactions for friends to send money to one another, cash money out at Standard Bank ATMs, use at accredited retailers, and make purchases from any SnapScan merchant in South Africa. Under the new name, Tencent Africa recently launched two new mobile products, JOOX, a mobile music streaming application, and VOOV, a social live streaming application.

When China’s Tencent brought its hugely popular instant messaging service WeChat to South Africa, it faced a near saturated market. To gain traction, Tencent Africa had to showcase WeChat’s versatility as a platform that goes far beyond just instant messaging. Engaging with local financial partners helped WeChat launch a WeChat Wallet to facilitate electronic payments, while providing exclusive content from South African cultural figures helped bring the platform extra publicity.

As WeChat started to grow its customer base, its on-premises infrastructure was stretched beyond its limits and the company looked for a cloud-based solution. After evaluating all its options, Tencent Africa found Google Cloud Platform best suited its needs.

“We’re a growing business and constantly upgrading our infrastructure. Getting new servers was becoming quite expensive so we wanted a cloud-based solution to reduce costs,” says Christoff Albertyn, Head of Technology at Tencent Africa. “When we did some latency testing, Google came out on top, so it made sense to go with them. Everybody loves Google, it’s a great brand. Just knowing a company like Google is behind it gives you peace of mind.”

Building a platform to scale

Instant messaging services need a stable infrastructure, the ability to scale at speed, and lightning fast performance. When Tencent Africa built an Official Accounts API to run a number of services on WeChat, to help companies engage with users on the platform, latency was its main concern. The Official Accounts services had to deliver replies over WeChat in under five seconds or the connection would drop.

Between the API on-premises servers in South Africa and WeChat’s main servers in China, Tencent Africa’s services regularly hit the limits of the permissible response time. In addition, by 2015, WeChat was starting to garner more customers across South Africa and Tencent Africa had to provision more servers. The on-premises servers were simply being asked to do too much, and expansion was proving expensive, so the company looked for a cloud-based solution.

Before committing to anything, Tencent Services did a thorough latency test of several cloud-based solutions. Google Cloud Platform came top. Tencent also engaged the help of Siatik, a Google Partner, to gauge what solutions best fit the company’s needs and help implement them. Siatik customers span both the public and private sectors and its consultants are regularly engaged in the health care, education, financial and technology industries. In order to provide leading technology solutions, it partners with industry leaders, such as Google, to provide best-of-breed infrastructure and cloud platform solutions to its customers.

“Siatik was a great partner to work with,” says Christoff. “Any questions I had, I could just pick up the phone and whatever it was they’d help me out. They were also able to get some of the team from Google to come to our offices and see how we worked, which was really good.”

With a simple, clean interface in Google Compute Engine, the company was able to spin up virtual instances very quickly and begin migrating its stack to Google. When it became more comfortable with Google Cloud Platform features, Tencent used Google Cloud SQL and Google BigQuery to manage its data streams, and Google Cloud Storage to store them safely.

From day one, it was very smooth. The interface was amazing—Google must have spent a long time perfecting it because it was so easy to use says Christoff. “I set up the first virtual machine in no time without any struggles.”

In addition to powerful hardware from Google Compute Engine, the fast, global network from Google helped to speed up performance. With the infrastructure ported over to Google, Tencent also brought in G Suite as an office productivity solution, which eased the pressure on its servers even more. Throughout the process, Siatik were on hand to advise and provide technical guidance whenever any issues came up.

What I really like is how quickly you can spin servers up. There’s no messing about and the interface is really easy to use, says Christoff. “You can have a virtual machine running in just a few minutes. It’s very impressive.”

Cutting costs, raising expectations

Google Cloud Platform helped Tencent Africa to slash its latency. Before the migration, pings to the Chinese servers and back would regularly take 180 milliseconds. Afterwards, this fell to around 35 milliseconds, helping to ensure smooth service to Tencent’s South African customers. Google offers innovative pricing, such as per-minute billing and sustained use discounts, which helped significantly cut server costs compared to an equivalent on-premises solution.

As its customer base grew, and Tencent Africa began to release new products, the ease of use of Google Compute Engine meant that spinning up new servers took minutes instead of hours and allowed the company to scale up and down at speed. Exploring products such as Kubernetes for rapid deployment or TensorFlow for machine learning, Tencent Africa continues to evolve and experiment with new products to keep WeChat a growing success in South Africa.

“Initially, we just used per-minute billing, but when I saw how much work we were doing with Google BigQuery and Google Cloud SQL, we started to generate sustained-use discounts, which helped save us a lot of money,” says Christoff. “The other great thing is, Google Cloud Platform monitors how you’re using it and tells you what else you can do to reduce costs.”

Cloud Retail Search, part of Discovery Solutions For Retail portfolio, helps retailers significantly improve the shopping experience on their digital platform with ‘Google-quality’ search. Cloud Retail Search offers advanced search capabilities such as better understanding user intent and self-learning ranking models that help retailers unlock the full potential of their online experience.

Google Cloud’s Discovery Solutions For Retail are a set of services that can help retailers improve their digital engagement and are offered as part of our industry solutions.

Executive Summary

Retailers are always working on trying to keep up with the ever changing consumer expectations and trying to forecast the next trend that can impact sales and revenue.

The pandemic brought its own (and largely new) set of challenges which further complicated the issue over the last two years. The retailers were forced to adapt to the new consumer (low physical touch) behavior in which the browsing and product research was largely digital (endless aisle) and accelerated other trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers. According to a McKinsey Global Survey from early last year, the pandemic has accelerated the pace of digital transformation by several years.

The National Retail Federation (NRF) estimates that retail sales are expected to grow between 6% and 8% in 2022 (slower growth rate than in 2021), as consumers spend more on services instead of goods, deal with inflation and higher food & gas prices due to geopolitical disruptions in the world.

And the competition continues to be fierce as ever. Amazon continues its dominance in the U.S. retail world and new PYMNTS data shows that Amazon’s share of US Ecommerce sales hit an all-time high of 56.7% in 2021.

Customers now have more choices than ever on how they want to engage with the retailers, where they want to spend the money and make their purchase. They also have increased expectations from the retailers around providing a high quality product discovery experience, which is forcing the retailers to invest heavily on improving customer engagement on their digital platforms to boost conversion rate and overall customer loyalty.

This is where Retail Search can help by providing an enhanced search experience that uses Google-quality search models to understand the customer intent and takes into account the retailer’s first party data (such as promotions, available inventory and price) for ranking results.

How is Google Cloud Retail Search Different

The Ecommerce platform on-site search use case is not new and retailers have been trying to solve it effectively for the last two decades. Most retailers recognize that search is a critical service on the platform and have spent countless resources to improve and fine tune it over the years. Yet the challenge remains. According to a Baymard Institute study in late as 2019, 61% of sites still required their users to search by the exact product type jargon the site uses.

However, users now expect the same robust and intuitive search features as is offered by Google.com and other popular web platforms, who seem to have the uncanny ability to intelligently interpret and yield relevant results to complex search queries.

Google’s decades of experience and research in search technology benefits Cloud Retail Search solution and that is what differentiates it from the competition.

• Advanced Query Understanding: Retail Search can provide more relevant results for the same query due to better query understanding features and knowing when to broaden or narrow the query results. While most search engines still rely largely on keyword based or matching tokens results, Retail Search has the advantage of being able to leverage Google search algorithms to return highly relevant results for product listings and category pages.
• Semantic Search: Intent recognition is a key requirement for semantic search and identifying what the customers mean when they enter the query is a key strength of Retail Search. This is critical for retailers since this has a direct impact on Clickthrough rate, Conversion rate and the Bounce Rate.
• Personalized Search Results: Another key differentiator for Retail Search is its ability to leverage user interaction data and ranking models to provide hyper personalized search results. Retailers are able to optimize search performance to deliver desired outcomes: better engagement, revenue, or conversions.
• Self-Learning and Self-Managed Solution: Retail Search models get better over time because of the self-learning capabilities built into the solution. In addition, the service is fully managed, which saves precious resources needed to keep it running and managing its set up.
• Strong Security Controls: The service runs on Google Cloud and follows security best practices to keep our customers’ data secure. Google never shares model weights or customer data across customers using the Retail API or other Discovery Solution products. For more details about this data use, see a description of Retail API data use.

High Level Conceptual View

Here is a simplified high-level view of Retail Search API. Retailers can call the API for the given search query and get back the results which can then be displayed on their digital properties.

The returned results contains two types of information:

• Search results: Query search results including product listings and category pages based on advanced query understanding and semantic search.
• Dynamic faceted search attributes: Faceted Search is a feature that allows further refinement of the search by providing ways to apply additional filters while returning results.

Retail Search needs the following datasets as input to train its machine learning models for search:

• Product Catalog: Information about the available products including product categories, product description, in-stock availability, and pricing.
• User Events: This is the clickstream data that contains user interaction information such as clicks and purchases.
• Inventory / Pricing Updates: Incremental updates to in-stock availability and pricing as that information is updated.

(Keeping the product catalog up to date and recording user events successfully is crucial for getting high-quality results. Set up Cloud Monitoring alerts to take prompt action in case any issues arise).

Retailers also have the ability to set up business/config rules to customize their search results and optimize for business revenue goals such as Clickthrough rate, Conversion rate, Average size order etc.

How to get started

Retail Search is generally available now and anyone with a Google cloud account can access it. If you don’t already have an account, you can start with a trial account for free here.

Establish a Success Criteria: It’s important to establish a success criteria for measuring the effectiveness of Retail search. Get a consensus on which factor(s) you want to include in scope for measuring the effectiveness of Retail Search. This could include one or two from the following: Search Conversion Rate, Search Average Order Value, Search Revenue Per Visit and Null Search Rate (No Results Found).

• Initial Set Up: Create a Google Cloud Project and set up the Retail API. When you set up the Retail API for a new project, the Google Cloud Console displays the following three panels to help you configure your Retail API project:
  • Catalog: displays product catalog and a link to import catalog.
  • Event: displays user events and a link to import historical user events.
  • Serving configs: contains details on serving configuration and a link to create a new serving configuration.

• Measuring Performance: Retail dashboards provide metrics to help you determine how incorporating the Retail API is affecting the results. You can view summary metrics for your project on the Analytics tab of the Monitoring & Analytics page in Cloud Console.

• Set up A/B Experiments: To measure the performance of Retail Search with another search solution, you can set up A/B tests using a third-party experiment platform such as Google Optimize.

Summary:

As retailers try to navigate through the post-pandemic world where supply chain failures and digital transformation acceleration are major focus areas, they now also have to keep a close eye on the recent geopolitical challenges resulting in rising inflation and costs.

While we can all agree that in-store shopping will continue to be a major source of revenue, it is also important for retailers to tweak the in-store experience for the digital world. Trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers are here to stay.

Given all the above, consumer engagement and digital experience is more important now than ever before. The cost of search abandonment is way too high and has both short and longer term impact. Retail Search is a great solution to help reduce churn, improve conversion and retention. It provides Google-quality search models to help understand customer intent and the retailers have the ability to set up business/config rules to optimize search results for business revenue goals such as Clickthrough rate, Conversion rate and Average size order.