Consider this approach to improve ROI for your paid search campaigns.
Ever wondered when and where you should draw the line on your paid search marketing investments? Or what are the important factors that have impacted the performance of your search campaigns? And how do you actually use Google Search Insights to drive meaningful information that can help you almost predict the future? Consider this an advanced article of paid search marketing.
Over many years in Asia, marketers have struggled to grasp the importance of budget caps and using impression share wisely. Yet, traditionally we are tuned to target 100 percent share of voice or something upwards of 80 percent - this brings a huge smile on our clients' faces.
However, to drive online sales we don't need to have 100 percent share of voice. Someone will not like me saying this.
(Based on internal campaign data, this chart provides an estimation of results. As you increase your daily budget and number of keywords (on x axis); how will it impact impression share and orders your campaign will generate?)
When you mix stats with business results you get a chart that many do not find easy to understand. However, it helps us find gaps and the right level of investments to make to drive a certain level of orders for your business. This is a classic case of using and improving ROI for your search campaigns.
Here is another example of using advanced stats to identify where your max leads are coming from. Using a very linear matrix, the chart exhibits that the bulk of the leads are currently driven by spends below $150. Anything above that is likely to give you some more leads but will also cost you more.
(Chart above represents at what daily spend is the bulk of your leads coming from. So if the client has to increase budgets, can they anticipate more leads or not?)
Given the long-standing relationship with statistics and paid search marketing, a whole lot of relations can be established in driving performance results for your search campaigns.
I only hope to see more of this happening in Asia as the market evolves.
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Prabhvir Sahmey (Prabh) heads the Media Platforms Business at Google India. In his current role, he is driving scalable growth for advertisers and agencies as well as efficiencies with their digital marketing efforts. This includes the entire DoubleClick stack for advertisers as well as the Real Time Bidding platform. With 10 years of experience in digital marketing, Prabh spent six years in paid search across various clients and industry verticals. He was previously with Mindshare leading the mobile and search practice for Singapore and established the Mindshare Center of Excellence for Search Marketing to enable attribution modeling and help clients understand digital via data driven marketing programs.
IBM Social Analytics: The Science Behind Social Media Marketing
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An Introduction to Marketing Attribution: Selecting the Right Model for Search, Display & Social Advertising
If you're considering implementing a marketing attribution model to measure and optimize your programs, this paper is a great introduction. It also includes real-life tips from marketers who have successfully implemented attribution in their organizations.
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