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Appier Celebrates 5 Years in AI

Appier celebrates our 5th Anniversary this year.  We share some milestones of the company’s progress in our journey towards Enterprise AI in this infographic.

Appier – then and now

Appier celebrates 5 years in AI

About Appier

Appier is a technology company which aims to provide artificial intelligence (AI) platforms to help enterprises solve their most challenging business problems. Appier was established in 2012 by a passionate team of computer scientists and engineers with expertise in AI, data analysis and distributed systems. Appier serves around 1,000 global brands and agencies from offices in 14 markets across Asia, including Taipei, Singapore, Kuala Lumpur, Tokyo, Osaka, Sydney, Ho Chi Minh City, Manila, Hong Kong, Mumbai, New Delhi, Jakarta, Seoul, and Bangkok. For more information please visit


Let us know the marketing challenges that you’re facing, and how you want to improve your marketing strategy.



Understanding the New Consumer Journey and Why It Matters

Reaching consumers was way easier in the 70s and 80s — the age of mass marketing. Today, the consumer journey is far more fragmented as they divide their time between different screens, which complicates the path to a buying decision. The savvy consumer now spends a significant amount of time on two or more screens every day. Globally and in Asia, device ownership continues to grow; more than half of Asian multi-device users (51%) now have two devices per person, while more than a quarter (26%) now operate on more than four devices. This means that marketers have to do things differently, even though the aim is still about reaching consumers at the point where they can influence the buying decision — also known as the consumer touchpoint. In the past, that touchpoint could have been through a TV ad at home, or in the newspaper. While this was simpler for the marketer, it also offered limited marketing options. The growth in devices adds complexity but it does open up new opportunities for marketers to influence consumer purchase decisions through different touchpoints in the consumer journey.   Why Cross-Screen Tracking is Hard In order to effectively reach today’s consumers, optimising

8 Best Practices to Maximize Your Profits With Upselling

What do well-known brands like Look Fantastic, Sky, InterContinental Hotels and Amazon have in common? They have all successfully used upselling as part of their marketing strategy to drive revenue. While upselling, or offering customers a more expensive or upgraded version of an existing product, is common practice, getting the most from it requires the right tactics. Instead of trying to win a new customer over, upselling targets people who have already bought your products or services. This means the attracting and convincing part of the sale is done, and you only need to give them a small push from buy to buy better, reducing marketing spend and increasing customer lifetime value. Not only is upselling more affordable than acquiring a new customer but also, according to Forrester, product recommendations are responsible for 10 to 30 percent of e-commerce site revenue. Even if you are only adding an extra dollar to each purchase, the profits add up. When done right, it should also feel like a win for customers. Check out these best practices you can apply to elevate your upselling game and maximize profits.   1. Map the Customer Journey The more you understand your existing customers, the more

Predictive Modeling: See the Future and Make More Profitable Decisions

Predictive modeling is considered a subset of artificial intelligence. Not only it can help businesses predict the future, but it can also propel growth. What is predictive modeling? How can it be applied in various marketing and business scenarios?   What Is Predictive Modeling? Predictive modeling is a process of creating a model to predict likely outcomes based on data collected from past and present events. The types of data used for prediction include transactional data, CRM data, advertising data, customer service data, economic data and demographic data. Predictive modeling can be used to predict anything from customer churn to credit risk, sports results and TV trends, making it easier for businesses to justify critical decisions, increase profits, and create a significant competitive advantage.   What Are Some of the Most Widely Used Predictive Models? There are several different types of predictive models and algorithms. Figuring out which ones are best for your business is essential to getting to most out of the process and to making informed decisions. Regression Model Regression algorithms predict a dependent variable based on independent variables. It is a way of mathematically figuring out which of those variables actually has an impact.  Classification Model The