Using Origins to support research about and engagement with Australia’s CALD communities

1. Using Origins to support research about and engagement with Australia’s CALD communities Uses, Applications and Privacy Compliance Michael Dove Principal Consultant, OriginsInfo

2. Introduction This PowerPoint slide show highlights a range of potential uses of Origins. It complements documentation found elsewhere in the OriginsInfo website regarding the privacy compliance of Origins data. See http://www.originsinfo.com.au/about/privacy. Please contact us directly at info@originsinfo.com.au if you need more information about why Origins data is privacy-compliant. Additionally, the slide show serves as support for current and potential clients considering the range of potential uses for Origins. Please note that the Office of the Privacy Commissioner (now the Office of the Australian Information Commissioner) has indicated to OriginsInfo that none of the potential uses of the Origins product is considered to contravene the Privacy Act.

3. Geographically aggregated Tabulation Mapping Profiling within the Origins software product Research and insight services Unaddressed non-personalised promotions targeted at small areas identified using Origins Non-personalised targeting of addresses identified using Origins Targeted prospect lists compiled using modelled multivariate selection criteria Lists compiled using Origins as a single selection Realtime coding for enhanced customer experience Customer segmentation Multipurpose use for research, insight, targeted communications and campaign measurement Potential Uses of Origins

4. 1 Aggregated dataProfiling areas Description This table shows a profile of name origins referenced to geographical areas, such as postcodes, SA1 areas, or similar. For each area, the percentage of names from each name origin group is identified. Uses A profile such as this helps organisations understand the mix of name origins at detailed geographical levels. Areas can be compared and ranked so that resources are allocated in the most efficient way. Typical Client Applications The Department of Health imports a table such as this into its mapping/GIS system to allow it to build up a detailed picture of name origins for any area (eg a health region, a hospital catchment, or a community).

5. Description This map shows the distribution of different name origins across a geographical area – in this case Melbourne metropolitan area. Uses A map like this helps organisations understand the city-wide mix of name origins across the urban area. Mapping is an important and effective communication device that is used to justify resource allocation in many different types of organisation. Typical Client Applications A large department store retailer can modify its product range in certain areas so that it is better aligned to the needs of particular cultural communities.

6. Description This map shows the distribution of people with names that originate in Vietnam. It also contains an underlay of areas showing the highest concentration of people with Vietnamese ancestry as indicated in the ABS census data. Uses The distribution of people with names of a particular origin provides a more granular view than is possible with census data. It also gives different, but complementary, information compared to the Country of Birth or Ancestry tables provided in the census. Typical Client Applications A big four bank is seeking to identify ways of improving the staff mix and language skills in its branch network. This information, when overlaid with the distribution of its branches, helps them recruit the right staff for the right locations.

7. 1 Greater Dandenong: Origins Map Description This map shows the distribution of different name origins in the City of Greater Dandenong. Uses A map such as this helps organisations understand the mix of name origins found in local areas. This information is used to guide resource allocation and helps improve provision of government services to ‘hard-to-reach’ communities. Typical Client Applications The City of Greater Dandenong can promote its library services to ensure that the service is accessed by all sectors of the community.

8. 2 Profiling within the Origins softwareCustomer profile (Count) compared with Australia (Base) Description This table shows part of a profile of Origins Types compared to a geographical base – in this case Australia. Profiling provides initial diagnostic research on how well people with different name origins are represented in an organisation’s customer list compared with the market from which they are drawn. Uses Profiling is a valuable way to find out if customers with particular name origins are under or over-represented (Index >100 = over-represented; index <100 = under-represented). Profiling is normally a first step for any public or commercial sector user with a list of customers or users of a particular service. Typical Client Applications A private health insurer uses profiling to understand how its brand appeals to names of different origin. Among other things, it also looks at the profiles of new members, cancelling members, members holding particular products, and payment methods.

9. 3 Research to provide behavioural insightPayment preferences: Index values with row and column counts Description This table shows comparative profiles of how customers prefer to pay their bills. The index values in the body of the table provide initial guidance about those preferences (>100 = Over-represented; <100 = under-represented). Uses Different payment methods have different implications for customer engagement, levels of service, cross-sell opportunities, and transaction costs. Understanding variation between different customer groups is a first step in managing towards preferred outcomes. Typical Client Applications A motoring services organisation has researched payment methods and identified that people with different name origins prefer to pay their bills in different ways. Their objective is to increase the number of members who pay on-line as this represents a lower-cost channel. Base = All Active Customers

10. 3 Research to provide behavioural insightConsumer satisfaction: Index values with row and column counts Description This table shows how responses from different name origins groups can be linked to responses on a customer satisfaction survey. Index values show the relative representation of different name groupings according to four different levels of satisfaction. Uses Helps organisations understand the cultural dimensions of customer satisfaction. Typical Client Applications A government department operates a citizen satisfaction survey. Origins provides the department with valuable insight into the cultural dimensions of consumer satisfaction. Base = All Consumers

11. 3 Research to provide behavioural insightEmployee diversity Description This table shows how name origins can be used to measure the extent of cultural diversity in the workplace. This type of analysis is used to identify how well the employee mix reflects the labour market or, indeed, the customer mix. Index values show the relative representation of different name groupings. Uses Helps an organisation measure how well it is practising equal opportunity in the workplace. Typical Client Applications A government department in Melbourne wanted to understand if certain segments of the community were under-represented. This research reveals a strong Anglo-Celtic bias in the current workforce, providing a useful benchmark for measuring future change. Base = Melbourne Adults

12. 4 Unaddressed non-personalised promotions targeted at small areas identified using Origins Description Many organisations distribute unaddressed information to small areas based on the characteristics of people living in those areas. The material may or may not be enclosed in an envelope but in all cases, there is no name on the material. All houses within the area will receive the same material, unless the letterbox indicates a preference not to accept unaddressed material. Uses This can be a very cost-effective way for government and commercial organisations to distribute information. Targeting increases the efficiency of reaching the right audience whilst keeping wastage to a minimum. Typical Client Applications After conducting research on current subscribers, a pay-TV company targeted areas containing a high proportion of people with names of Greek and Chinese origin.

13. 5 Non-personalised targeting of addresses identified using Origins Description Some organisations find it cost-effective to recruit customers by door-knocking in areas containing a high proportion of potentially attractive customers. Uses Origins identifies addresses most likely to contain people with name origins that belong to the desired audience. This increases efficiency and effectiveness of door-knocking, particularly in low-density areas where the distance travelled between the front doors of houses would otherwise make such an approach inefficient and impractical. Typical Client Applications For the electorate of Bennelong in the 2007 federal election, the ALP targeted people with names of Chinese origin because it was felt that securing their vote could be decisive for the electorate as a whole. Culturally ‘compatible’ door-knockers were also part of the ALP’s successful strategy to pro-actively engage with that community and win the seat for Mary Delahuntly against John Howard. Example A metropolitan city council identified that the Chinese community was under-represented in the use of the city’s child care services. In an attempt to improve access to its services to all members of the community, the city council decided to promote its services to people with names of Chinese origin. Direct engagement was known to be the most effective way of informing community members of the services. Addresses with a high likelihood of Chinese residents were identified for a targeted door-knock campaign aimed at raising awareness of the council’s services.

14. 6 Targeted prospect lists compiled usingmodelled multivariate selection criteria Description The most sophisticated targeting occurs within large organisations, such as those in the finance, telecommunications, and insurance sectors. Often with the aid of an external solutions partner, each customer is evaluated across a range of behavioural and demographic indicators, one of which may be Origins. Uses Predictive models are an essential part of efficient and effective customer management and the delivery of customer service. Typical Client Applications An energy retailer wanted to identify those customers most at risk of defecting to a lower price competitor. It built predictive models identifying those most likely to ‘churn’ to the competitor. Name origin was identified as a key predictive indicator. A statistical model was built to allocate a score to all customers and flag those customers who were most at risk of churn. The model allows them to target those customers with information and offers that are designed to promote their loyalty. • Example • To support a promotion for housing investment loans (product X) targeted at the most appropriate existing customers • The selection of customers was based on the following characteristics of customers who, historically, have had a good take-up rate for this product: • Not having product X • Being a customer for less than five years • Maintaining a positive credit history • Origins codes – Customers with names originating in Southern Europe • Likely to be aged under 45 • 75% more likely to be male • Lifestyle Groups A, B, D, G

15. 7 Lists compiled using Originsas a single selection Description This table shows a list of names that are most likely to be of Chinese Cantonese origin. Lists can be compiled to reflect the most likely backgrounds for any broadly defined community. Uses Targeting a group with a particular name origin can generate many positive outcomes for businesses and customers. The communication can be crafted to be culturally-relevant and appropriate, reinforcing a customer’s sense of identity. Customer survey panels can be constructed to be representative across the range of name origin groups. Typical Client Applications A large financial institution wanted to improve its engagement with customers of Islamic background. It constructed a product with relevant features – eg no interest earning during Ramadan – and mailed a targeted, culturally-relevant communication to key prospects.

16. 8 Realtime coding for enhanced customer experience Description This chart shows the process of how a client would use Origins Realtime to engage better with a particular cultural groups. Uses More personalisation and better targeting add relevance to communications and achieve greater efficiency in the promotion of goods and services. Consumers experience improved service through communication with people who are more culturally competent. Typical Client Applications A private health insurer seeks to better engage with Chinese customers. After a name is entered on an enquiry form, realtime coding indicates those who are most likely to be of Chinese background. In the call centre, the enquiry can then be routed to a customer service agent who is culturally competent in dealing with Chinese people. The agent can then provide information about products , features and offers that are best suited to people with a Chinese background. In addition, the tone in the language (even if in English) will be better aligned with Chinese cultural expectations .

17. 9 Customer segmentation Description Most large consumer-facing organisations group their customers into distinct segments based on a range of internal transaction history and external data elements, one of which may include a name origin code. Uses Segmentation helps organisations understand groups of customers better so that their diverse needs can be better met. Using this resource, a client can develop solutions and communications that are optimised to the characteristics of the group. Typical Client Applications A large loyalty card-based retailer wanted to combine a range of geodemographic data with its own product purchase history and transaction records. The retailer selected Mosaic, a market-leading geodemographic system and a name analysis coding tool because it knew that its products were more appropriate to members of some cultural communities than others. The resulting segmentation enabled them to create products, communications and offers that were tailored to the characteristics of different segments.

18. 10 Multipurpose use for research, insight, targeted communications and campaign measurement Description This table shows a sample extract from a customer database indicating how the Origins data would appear in a table form. Uses Using this resource, a client would be able to readily create a set of customers for ad hoc analysis – eg identifying the name origin mix of those customers who were entitled to a government grant. Typical Client Applications A government department wanted to understand if there was a cultural skew in the take-up of grants to assist with child care costs. The department needed an evidence base to justify an in-language campaign targeted towards unrepresented groups. The plan also included analysis of campaign response rate by name origin group to assess the effectiveness of government spend.