 "Retargeting redefined")
In today's era of digital marketing, advertisers have access to innovative tools and platforms, which enable them to provide internet users with more personalised ads. Furthermore, in exchange for such helpful and free service, people do not mind sharing a little bit of personal information as it helps them find products that match their preference and also save them time and money. To ensure customers get interesting or relevant ads when surfing for products online, advertisers leverage online behavioural advertising (OBA).
In an OBA model, advertisers harness customers' information from mediums such as web, mobile and social media to understand their online and real-time behaviour and accordingly target them with relevant ads. By doing so advertisers ensure their advertisements make a maximum impact on the general public, which in turn increases purchase of products and services, thereby, increasing the marketer's bottom line.
With the kind of benefits it has to offer advertisers, it is not surprising that OBA is big money, especially with companies like Facebook, Google, and Yahoo! making the most it. To put this in perspective, consider the incident that occurred last September when Facebook had an outage for 18 minutes. Per minute, Facebook generates about $22,000, so during the outage they possibly lost $400K. This amount may look miniscule when compared to Facebook's annual revenues, but if you add in all the lost revenue from all the businesses that generate ad revenue on Facebook's platform, a lot more than $400K was lost.
As platforms such as Facebook, Google, and Yahoo! have become universal content and media platforms, advertisers need to deal with the implications of convergence in the digital realm. Additionally, businesses have started capturing online and real-time data independently, to target customers with relevant products. For instance, most organisations that have a mobile app now capture and track geo-location information that can be used to suggest a relevant product. This has also changed the business realm to a more collaborative business ecosystem where data can be captured across internal sources like CRM and external sources like Facebook and converged. This convergence allows one channel to leverage features and benefits offered through other channels. The convergence of multiple channels and platforms makes it imperative for advertisers to take a holistic view of their environments.
In addition to convergence and keeping a track on what user's click, post, like, and comment on, it is also necessary advertisers integrate and analyse all the resultant big data and use this information to better target online users. This big data is a collection of information from an array of sources including CRM, transactions, online digital analytics, advertising offerings, and data management platforms.
Obtaining a holistic view of customers is indeed a classic big data problem as advertisers need to capture, prepare, manage, integrate and analyse huge amounts of digital data coming in rapidly from a variety of sources. But the good news is that developments in advanced analytics, data visualisation and big data processing power can make the task easier. Analysing data from multiple sources not only provides insights to advertisers on how consumers interact with brands and content, but also enables them to discover something new about the customer's behaviour. Additionally, platforms available today enable deriving the insights on consumers and acting on these insights in real-time to create the maximum impact.
As advertisers work towards understanding the customer's behaviour and targeting with relevant ads they should also learn to respect these new insights and the customers' privacy. Though it is tricky, advertisers need to find the right balance between honouring people's privacy while providing them with a relevant online experience.
In an OBA model, advertisers harness customers' information from mediums such as web, mobile and social media to understand their online and real-time behaviour and accordingly target them with relevant ads. By doing so advertisers ensure their advertisements make a maximum impact on the general public, which in turn increases purchase of products and services, thereby, increasing the marketer's bottom line.
With the kind of benefits it has to offer advertisers, it is not surprising that OBA is big money, especially with companies like Facebook, Google, and Yahoo! making the most it. To put this in perspective, consider the incident that occurred last September when Facebook had an outage for 18 minutes. Per minute, Facebook generates about $22,000, so during the outage they possibly lost $400K. This amount may look miniscule when compared to Facebook's annual revenues, but if you add in all the lost revenue from all the businesses that generate ad revenue on Facebook's platform, a lot more than $400K was lost.
As platforms such as Facebook, Google, and Yahoo! have become universal content and media platforms, advertisers need to deal with the implications of convergence in the digital realm. Additionally, businesses have started capturing online and real-time data independently, to target customers with relevant products. For instance, most organisations that have a mobile app now capture and track geo-location information that can be used to suggest a relevant product. This has also changed the business realm to a more collaborative business ecosystem where data can be captured across internal sources like CRM and external sources like Facebook and converged. This convergence allows one channel to leverage features and benefits offered through other channels. The convergence of multiple channels and platforms makes it imperative for advertisers to take a holistic view of their environments.
In addition to convergence and keeping a track on what user's click, post, like, and comment on, it is also necessary advertisers integrate and analyse all the resultant big data and use this information to better target online users. This big data is a collection of information from an array of sources including CRM, transactions, online digital analytics, advertising offerings, and data management platforms.
Obtaining a holistic view of customers is indeed a classic big data problem as advertisers need to capture, prepare, manage, integrate and analyse huge amounts of digital data coming in rapidly from a variety of sources. But the good news is that developments in advanced analytics, data visualisation and big data processing power can make the task easier. Analysing data from multiple sources not only provides insights to advertisers on how consumers interact with brands and content, but also enables them to discover something new about the customer's behaviour. Additionally, platforms available today enable deriving the insights on consumers and acting on these insights in real-time to create the maximum impact.
As advertisers work towards understanding the customer's behaviour and targeting with relevant ads they should also learn to respect these new insights and the customers' privacy. Though it is tricky, advertisers need to find the right balance between honouring people's privacy while providing them with a relevant online experience.
The author is Sudipta Sen, regional director, South East Asia, vice-chairman and board member, SAS India.
Reprinted with permission.
Link: http:// blogs.sas.com/content/anz/2015/03/27/leveraging-analytics-for-a-successful-online-behavioural-advertising-strategy/
Reprinted with permission.
Link: http:// blogs.sas.com/content/anz/2015/03/27/leveraging-analytics-for-a-successful-online-behavioural-advertising-strategy/