New Zealand
New Zealand New Zealand
Consumers make most of their payments by internet banking
  • 74%
    BFSI
  • 70.5%
    TELCO
  • 54.5%
    RETAIL
  • 46.5%
    BFSI
  • 39.6%
    TELCO
  • 40.7%
    RETAIL
  • A higher percentage make payments via internet banking to banks and insurance companies, telcos, and retailers, respectively, compared to the regional average
  • Impact: Anti-fraud capabilities critical to the increased digital transaction frequency and customers’ trust in banks
Australia
Australia Australia
Consumers are most satisfied with the post-fraud service of banks and insurances companies
  • More than 70% satisfaction rate compared to 59.7% on average
  • Impact: Increased trust in BFSIs
Indonesia
Indonesia Indonesia
Consumers that encountered most fraud incidents in the past 12 months
49%
34.7%

AP Average

  • 49.8% have experienced fraud at least once compared to 34.7% on average
  • Impact: Overall anti-fraud capabilities need improvement
Singapore
Singapore Singapore
Consumers have the highest trust towards government
AP Average
  • 75.5% choose government agencies, compared with 51.7% on average
  • Impact: Trust of personal data protection is centered around government agencies
Vietnam
Vietnam Vietnam
Consumers encountered most fraud incidents in retail and telco during the past 12 months
  • 55%
    TELCO
  • 54.5%
    RETAIL
  • 32.8%
    TELCO
  • 35.2%
    RETAIL
  • 55% and 54.5% have experienced fraud at least once in retail and telco, respectively, compared to 32.8% and 35.2% on average
  • Impact: Overall anti-fraud capabilities need improvement
Thailand
Thailand Thailand
Most Thai consumers believe speed and resolution are severely lacking (response/ detection speed toward fraud incidents)
AP Average
  • 60.5% think it is most important, compared to 47.7% on average
  • Impact: Response time as one of key factors to fraud management to retain customers and gain their trust
India
India India as standalone
Consumers have the largest number of shopping app accounts in the region
India
  • Average of three accounts per person
  • Impact: Highest exposure to online fraud
Hong Kong
Hong Kong Hong Kong
The least percentage of consumers with high satisfaction level toward banks and insurance companies’ fraud management
AP Average
  • Only 9.7% are most satisfied compared to 21.1% on average
  • Impact: effective response towards fraud incidents to be improved
China
China China
Consumers are the most tolerant toward submitting and sharing of personal data
AP Average
  • 46.6% compared to the AP average of 27.5% are accepting of sharing personal data of existing accounts with other business entities
  • Impact: higher exposure of data privacy and risk of fraud
alert
Japan Japan as standalone
Consumers most cautious on digital accounts and transactions
50.7% Actively maintain digital accounts’ validity
27% AP Average
45.5% Do not do online bank transfers
13.5% AP Average
  • More than 70% did not encounter fraud incidents in past 12 months, compared to 50% on average
  • Impact: Relatively low risk of fraud

Fuel quicker growth, with deeper customer insight

Fuel quicker growth, with deeper customer insight

When looking to support business growth, typically a great place to start for organisations is to understand who has purchased from them before. On the surface that might seem obvious and not too overwhelming. In this article we will take a closer look into how the combination of data and technology, through a tool such as Experian’s Mosaic, can help accelerate a shift towards deeper customer insight.

 

Understanding who your customers are now

 

Typically, an organisation looking to develop a growth strategy will begin with a market sizing exercise to determine the pool of potential customers. For example, at a very high level this might begin with the 25 million people that make up Australia.

 

Taking this a level deeper, organisations will probably perform some basic grouping exercises. Segmentation of customers based on age, sex, or something else will help identify key trends. Taking the age example, if we plot the distribution of age groups, trends will appear about the age of the people purchasing products. Organisations may sell predominantly to under 40s for example, with far less penetration at older age groups.

 

This seems all well and good. Organisations then pass the key pieces of information to Sales and Marketing and they can start targeting their outreach.

 

But do we have enough contextual insight to  inform a high quality targeting decision yet? Probably not.

 

If we continue to explore this idea of segmenting customers based on their age, what other data can be used to give our analysis real credibility? Let’s revisit the 25 million people in Australia. If we layer that data over our age groups we will now have some context regarding the proportionate relationship between the two data groups.

 

Immediately this may flag some interesting insights. The under 40s group that looked so appealing originally may be proportionally underrepresented when held against the national age groupings. Even more interestingly, (and remember this is an example) we can now see that a small group of customers in the 60+ age group are significantly overrepresented versus the national averages.

 

So let’s look at the relationship between those two groups in more detail by indexing the data. Through this process we establish that the 60+ group are almost twice as likely to be a customer versus the national average. Suddenly, the 60+ age group becomes very attractive. Something that was not at all evident in the initial age group analysis.

 

We have provided context to our customer segmentation data analysis.

 

Understanding who your customers will be next

 

If we continue with our example where we established the over 60 age group is actually a high value segment. Now we need to analyse the data against a comparison segment.

 

This is where Mosaic, by Experian, comes in.

 

Mosaic layers comprehensive information about every household in Australia on top of an organisation's existing customer data, giving unprecedented insights into who the best customers are, how they think and act, and how to reach them.

 

Mosaic contains 14 Groups and 51 sub-groups, called Types which segment the Australian population and can be used to further understand which people in high value segments are the most appealing based on their behaviours and lifestyle choices.

 

Mosaic then takes things a step further, allowing organisations to target the Groups and Types within their high value segments specifically.

 

Suddenly, we have a very compelling GTM strategy forming. We can see groups of high value customers, we understand their representation and we now know specifically who is most likely to purchase from us in the future. A great result.

 

For more information about how Experian Mosaic can revolutionise your sales and marketing efforts, please visit our Mosaic Page or complete your details below.

Read full article

Experian

By Experian 05/21/2021

Related Articles

How data validation integrations improve efficiency
How data validation integrations improve efficiency

This past year has been overwhelming for retailers across the globe. In fact, many have had to become more innovative than ever before—they’ve grown their eCommerce operation and maximised marketing…

Learn more
Launching our first Global Diversity Equity and Inclusion Report and the 2021 Sustainable Business Report
Launching our first Global Diversity Equity and Inclusion Report and the 2021 Sustainable Business Report

We sit in a pivotal position in the societies where we operate. For us, using our expertise in data to help tackle big societal issues, is much more than an…

Learn more
Removing the debt stigma
Removing the debt stigma

Considering that debt can be used to describe anything from a house mortgage or overdraft to even an unpaid bill, we can all relate to ‘owing money’ in some way.

Learn more

  • Submit
By providing your personal information you agree that we may collect and process it in accordance with our Privacy Statement.