Singles Day: Reduce Acquisition Costs by 53% with Lookalike Targeting
China’s Costly Customer Acquisition Problem
Soaring customer acquisition costs (CAC) has made China one of the most difficult markets in the world for brands to build their customer base. For example, in 2013 the cost of acquiring a new customer on the Taobao platform was 30 RMB ($4.33 US) and by 2017 this had risen to 250 RMB ($36 US). As of Q1 of 2020, the average CAC for all of the Alibaba Ecommerce platforms (Taobao, Tmall, etc.) had reached a staggering 812 RMB ($117 USD), vexing CMO’s and diminishing any margins for error.
No period is more costly and crucial for brands than the November 11th (11.11) Single’s day event, the ‘biggest shopping day on the planet’. In 2019, Alibaba claimed that sales of goods on its combined platforms exceeded 268 billion RMB ($38.6 billion US) and over 300 brands sold more than 100 million RMB($14.3 million US) in gross merchandise value. Over this period, it's common for brands to spend 20-30% of total revenue on customer acquisition and marketing. The Singles day event and its less glamorous 12.12 little brother, are high stake’s games for marketing departments forced to gamble a significant share of budgets and resources over a short-time period if they are to make revenue targets for the year.
Preparing for Singles day (11.11) and 12.12
Brands and especially CMO’s can now no longer risk making any mistakes over the two juggernaut retail festivals. With advertising and customer acquisition costs so high, marketing budgets need to be governed with parsimonious iron fists. Shrewder decision makers are now already planning well in advance for 11.11 and 12.12..
Why Most Advertising Targeting in China Doesn’t Work
One of the main reasons that foreign brands fail in China is that they underestimate the difficulty of the market and don’t understand enough who their customers are. The result is advertising overspends with poor results.
The China market is too complex and vast for the standard demographic and interest targeting used elsewhere. Say for example, a brand wants to target the segment of Generation Z Males (born 1995-2002), we are talking about a cohort of around 180 million people, 35 million more than the whole population of Russia.
Unless your advertising is precisely targeted, you are going to burn through cash fast and this is especially true in the noise of the 11.11 and 12.12 festivals, when every single brand on the planet is clambering for shopper’s bandwidth.
Lookalike Targeting is the Answer
Lookalike targeting is when audiences are assembled algorithmically, based on their similarity in terms of interests and behaviors with a preset seed, which usually consists of existing customers. The advantage of this is that brands are able to run ads for highly-qualified audiences that would have been previously hard to reach.
This approach presents a number of clear advantages for brands:
- Expands potential advertising audiences to differentiated populations.
- Reduces the influence of human bias, with the algorithms uncovering potential customers that would go unseen by humans.
- Saves time studying consumer behavior and increases operational efficiency.
- Ultimately, saves money by lowering customer acquisition costs and improving return of investment
This represents a winning situation for foreign brands in China who lack the knowledge of market intricacies that their local competitors might have. The algorithms relieve them of the barriers of cultural blindness and allow them to scale beyond their local environment.
The other key advantages for overseas brands in China is that they can easily prospect new audiences through testing metrics, before scaling up when they confirm that they have the right audience. To be able to confirm that the cost for lookalikes will be worthwhile, it's crucial to test and compare the different audiences. The costs for testing audiences is generally low and brands are able to ensure that they will be profitable before investing money.
Taeltech Presents Lookalike Targeting 2.0
Understanding the anxieties of overseas brands competing in an increasingly challenging and costly Chinese e-Commerce landscape, Taeltech launched a lookalike ad optimization tool to generate superior targeting for ads. Taeltech is the largest independent ecosystem connecting people and consumer products.
Taeltech lookalike targeting is built on AI algorithms that leverages a vast pool of millions of regular consumer interactions (shopping, scanning barcodes, answering surveys, sharing with friends etc.). Also boasting deep holistic consumer profiles that cross channels, ecosystems and categories.
The benefits for partnered brands over other lookalikes are:
- Deeper Understanding of Users: When brands use their own lookalike seeds, the only information they have are users purchasing history and some basic demographic data. Taeltech is able to leverage much wider consumption baskets and behavioural traits through amalgamated tracking of cross-category shopping behaviours, users scanning barcodes of products they have at home, as well as regular surveys.
- Taeltech Lookalikes Audiences Actually Want to Buy Your Products: standard algorithms create lookalikes based on your best customers and the assumption that your best customers are the ideal target.
Taeltech can use the example of cars to illustrate the danger in this standard approach. If you were to build your lookalikes based on the customers who bought cars in the last 2-3 years, these customers don’t probably need a car as they are happy using their existing one.
Taeltech lookalike audiences contain people who read and discuss things like “what’s the warranty on Car Brand X?” or “Which family SUV holds its value best?”. In effect, people who are clearly looking to buy a car. This is what our algorithms do. These kind of algorithms have already been utilized by major companies such as Amazon.
Lookalike Targeting Lowers Customer Acquisition Costs by 53%
Taeltech has successfully utilized ad optimization algorithms and lookalike audience tools to improve advertising performance for a platform selling imported products in China. Click-through rates increased by a dramatic 267% (from 0.3% to 1.1%). Similarly impressive, customer acquisition costs reduced by 53% (from 495 RMB to 221 RMB).
The process of working with Taeltech is simple, and can be tailored according to requirements (please see diagram below).
Win on 11.11 and 12.12
Taeltech’s lookalike audience algorithms can help brands get better performance on social media ads in China. As mentioned, the time to prepare for 11.11 and 12.12 is right now. Now is the time to run tests on lookalike audiences before the event, so that you can maximize return on marketing budgets and avoid unnerving customer acquisition costs.