Understanding the New Consumer Journey and Why It Matters

Understanding the new consumer journey

By Fabrizio Caruso, Chief Revenue Officer, Appier

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 campaigns across all screens is a must. However, marketers need to overcome two challenges in understanding the consumer journey:

  1. Understand the ownership of multiple devices by the same consumer, in order to switch from a device-centric to a consumer-centric approach.
  2. Know which channel the consumer prefers, and the preferred touchpoint where the buying decision is made. This could be at the buy phase, or earlier when the shopper is wondering whether to buy, or when they are doing research and evaluations.

Marketers also need answers to these questions:

  1. How much overlap is there between devices?
  2. How can the right amount of engagement be achieved at the right frequency to spur consumers to take action on your brand?
  3. How much is harmful – wasting money or consumer goodwill?
  4. Which devices are best for driving upper funnel exposure, and which are best for direct action campaigns?

Artificial Intelligence (AI) technology can provide insights into the number of users, where and on what screens they viewed an organisation’s ads, and cross screen conversion paths. Insights can be gleaned into the role every screen played in the customer’s journey — not just the last screen they used before clicking the ad.

This allows marketers to optimise their brand assets to each screen to receive higher ROIs— whether it is click-through rate, engagement or conversion.

Drive more consumer purchases

When global retailer Carrefour expanded online, it wanted to reach more potential consumers through its online store. The marketing team wanted to boost awareness and drive more online purchases, while optimising the cost per action (CPA).

The use of Appier AI technology helped Carrefour identify all devices owned by the same user from billions of data points. When a potential buyer visits the Carrefour online store on one device (e.g. a laptop), Appier could analyse his or her profile and deliver customised product recommendations on other devices owned by the same person (e.g. a phone), motivating the person to buy from the Carrefour online store.

Appier’s AI analyses user behaviours both within and outside of the website to determine the activities of a single user as well as to segment different users. Cross-comparisons with the Appier CrossX database along multiple dimensions allow Appier to locate potential customers in similar segments to expand the original user base.

Through this partnership with Appier, Carrefour experienced click-through rate (CTR) of cross-screen users that was 87% higher, and a conversion ratio (CVR) that was 40% higher, than for single-screen users.

Drive more subscriptions

Using AI, popular dating app Paktor managed to drive more in-app subscriptions while increasing the in-app tutorial completion rate.

The Appier AI technology quickly identified users’ cross-screen behaviors and their interests in “socialising and dating” from billions of data points.

After the potential buyer downloads the Paktor app, Appier re-markets social/dating-related information to every device owned by the same user through a cross-screen approach. This deepens the Paktor brand impression and helps to trigger the motivation to become a Paktor VIP member.

Brand Safety Woes

Besides reaching and engaging customers, brand safety has also become a key concern with digital marketing, as organisations worry that their online ads may appear in a context that will damage the their brand.

While there are different aspects of brand safety, one key area is ad fraud, where online ad impressions, clicks and conversions are fraudulently represented in order to generate revenue.

AI can fight ad fraud and help protect brand safety. A study by Appier found that an AI-based fraud detection model was able to identify twice as many fraudulent transactions as a traditional rule-based model, as it is able to pick out ad fraud patterns that are difficult for traditional models to detect.

Now what?

With the revolution in the way consumers make buying decisions, using the right approach can help marketers be at the right place at the right time in the consumer journey.

How are you optimising your campaigns across all screens? If you want to know more about driving more click-throughs/conversions or to do more for your brand safety, get in touch today.

About the author:

Fabrizio CarusoFabrizio Caruso is Chief Revenue Officer of Appier. With over 15 years of experience in the digital and mobile industry, Fabrizio has established strong partnerships with top-tier brands and agencies, mobile operators and media companies in Asia. Fabrizio has engaged in management, planning, marketing and operational activities in the mobile payment, mobile internet content and mobile advertising industries. With insider knowledge of wireless and internet technologies, Fabrizio is also a frequent public speaker and author.

Before joining Appier, Fabrizio served as Senior Vice President Asia at Opera Software, a leading mobile internet and advertising company. Prior to that, he served as Managing Director for Asia-Pacific & Vice President for Business Development at Out There Media and held senior management positions at Buongiorno and Amdocs in the United Kingdom, China and the Philippines.

How Artificial Intelligence can Help Enterprises Gain Insights into Asian Consumers

By Jennie Johnson, Head of Marketing, Appier

Artificial intelligence (AI) is without doubt one of the most talked-about technologies today, and for good reason: advances in computation, processing power and storage, and the tremendous volumes of data generated, thanks to new mobile and cloud technologies have come together to drive a renaissance in AI.

On the other hand, this confluence of factors is also creating mountains of data – and a headache for any enterprise trying to make sense of all of it. Since Appier was established five years ago, we’ve accumulated a considerable database of billions of anonymized device profiles in Asia, which continues to learn as it grows. This data provides some very good insight into the cross-screen behaviors of people throughout the Asia-Pacific region.

Today, I wanted to share a few highlights from our newly-released 2H 2016 Cross-Screen User Behavior Report, generated from our analysis of over 1,800 billion Appier-run campaign data points.

Appier 2H 2016 Cross-Screen Report

For enterprises, one of the report’s key takeaways is just how important it is to understand the cross-device dynamics of today’s consumers. The complexity of these usage patterns make it difficult for marketers trying to reach them using conventional technology. Using AI, Appier is able to process these billions of data points quickly, detect patterns and even predict future behavior.

I encourage you to download the report to read at your leisure, but I wanted to share here a few key trends the report reveals.

1. A cross-device perspective is critical to understanding Asian consumers

51% of internet users across Asia own 2 or more devices. And among that group, more than half (26% of total users) regularly switch between four or more devices. Regionally, Taiwan users lead Asia in multi-device usage, with 40% using four or more devices, followed by Australia and Japan (29%), Singapore (28%) and Hong Kong (27%).

There’s a lot of talk about the importance of mobile in Asia, but the data from our report shows clearly that a single-device perspective provides an incomplete view of how users in Asia are interacting online. A cross-device perspective is essential for a complete understanding of the user journey.

Consider this: more users browse websites on their PCs during the work day than on mobile, even here in mobile-crazy Asia. But at night, this trend reverses. To be even more precise, our data shows that pageviews on PCs are highest between 2 and 3 pm while pageviews on mobiles peak between 9 and 10 pm.

Screen Shot 2017-09-04 at 3.50.20 PM

Another important point the report reveals is just how differently users in Asia reacted to online ads, depending on which device they were using. On average, 79% of users exhibited different behaviors across devices. 35% of users showed completely different behaviors. There are also important differences in this user behavior across the region: Korea logs the most varied behavior at 88%, while on the other end of the scale, Hong Kong stands at 51%.

2. Linking usage data across devices is essential for a comprehensive enterprise data strategy

As our report shows, only by viewing data across devices can you see a complete picture of your user’s journey, and only then will you be able to plan your marketing campaigns effectively. This level of detail is important for marketers, but it’s instructive for other parts of the enterprise as well. For example, the human resources department can use AI to determine where best to deploy the workforce to better serve the needs of the customer base or to identify key skills which HR requires.

3. Richer data sets lead to higher performing campaigns with greater ROI accuracy

Our data consistently shows that cross-screen campaigns perform better than single-screen campaigns. Click-through rates in Vietnam was 54% higher for cross-screen campaigns, while in Australia, the difference was 53%; in India, 48%; in Taiwan, 36%; in Hong Kong, 27% and in Japan and Korea, 19%.

Using Appier’s AI platform, we were also able to help our customers accurately identify the final conversion device on cross-screen campaigns, a critical piece of information for marketers. Across Asia, the smartphone accounted for 46% of final conversions. As usual, there were significant differences by country. The PC drives most final conversions In Australia (71%), India (41%), Malaysia (44%) and Vietnam (41%). The smartphone served as the final conversion device in all other countries – Hong Kong (48%), Indonesia (64%), Korea (62%), Singapore (53%) and Taiwan (48%).

The richer the data, the more successful the campaign. Our research shows three screen campaigns deliver as much as 160% more conversions than those on two screens.

4. Predicting actions is where AI truly shines

We have long believed that one of the biggest benefits of AI is helping predict future actions. Through a comprehensive analysis of the rich datasets that we have accumulated over the years, we have been able to help our customers with very precise and accurate predictions of what their target audiences will do.

One exciting area that we’re exploring is Aixon, a data intelligence platform that allows marketers at a variety of enterprises to discover new customers, enrich their understanding of their customer base, and make predictions using AI.

Some examples of ways that enterprises can use Aixon include:

  • A news publisher looking to increase their online subscriptions by identifying likely subscribers online.
  • A marketer analyzing data to discover what topics their users are interested in and integrating these insights into their CRM system to optimize their content strategy.
  • An e-commerce merchant driving more online sales or conversions by analyzing site data to predict which users are most likely to make online purchases.
  • A mobile app developer identifying users at risk of uninstalling their app so they can plan and implement re-engagement measures.
  • An online publisher increasing the value of their inventory by providing more granular analyses of site audiences to potential advertisers.

Final word

For more data, details, and insights to consumer behavior in Asia, go ahead and download the report. If you’d like to learn more about how AI can help you, don’t hesitate to get in touch with us for more information. Appier’s AI has been helping our customers navigate the complex, cross-device consumer space in Asia over the last five years but this is just the beginning. We believe AI has more to offer to enterprises.


About the author:

Jennie Johnson

Jennie Johnson is Head of Marketing at Appier. She oversees public relations, online and offline marketing, content and design. Prior to Appier, Jennie led a wide variety of consumer and business-facing product communications for Google across 14 markets in Asia and the US. Her last role at Google was leading a regional team devoted to building and sharing stories about how Google helps Asia’s businesses grow online. Jennie graduated from Harvard University with a Bachelors of Arts in East Asian Studies.

Editor’s note: This is the first post of our revamped Blog. Please stay tuned for more insights into enterprise artificial intelligence (AI) from Appier’s leadership team and other thought leaders from the industry. To re-print or re-post this blog, please write to [email protected]