In September of 2007, Google announced this brand new interactive advertising for advertisers to experiment with new interactive media formats. These new Gadget Ads can incorporate real-time data into the ad so that the content becomes more relevant to users and websites. Instead of simply clicking through an ad to a website, with gadget ads the consumer can click a certain area, learn more about the advertisers right there, and decide to continue. Due to this interactive format you can track your ad on basis of Ad viewed, Interacted with, Interacted with to a certain extent, and many more. Within the Gadget Ad you can specify interaction triggers so you can track all sorts of interaction very easily and a completely customizable, flexible manner. These triggers will appear in your detailed tracking reports provided by Google. The pricing model is similar to AdWords where you can use CPM/CPC, use geographic targeting, etc.

In contrast to regular ads where you just need an image or text, with Gadget Ads you actually need to develop them by writing a code. Basically you’ll be using lots of AJAX and Flash. Also, you can use Google’s online tool called the “Google Gadget Ad Editor” to write code online and for testing purposes.

You can host the Gadget Ad directly on your server and Google will request it once and then automatically cache it. This will reduce load on your servers while still displaying updated advertisements to the users.

Similar to Linkedin begins with B……

The report revealed the following:

•       Heavy clickers represent just 6% of the online population yet account for 50% of all display ad clicks.
•       Heavy clickers represent the active surfer and are not representative of the general public.

 In India, this active population of the internet audience is even smaller and hence the conclusion whether an online display or content communication (based only on clicks) has worked or not will be of extreme unfair proportions.

 How does one measure the effectiveness of an online display ad?

1. a.      Sales/Search Impact analysis:

Has the display resulted in increased search volume or increased sales? It would be difficult to answer that question since search or sales volumes are very prone to offline advertising, promotional and seasonal impacts. A decision like that will have to taken after discounting any seasonal impact.

1. b.      Engagement Impact analysis:

Have users been spending more time on your site? How many page views have they had? But considering the reservations regarding percentage of active users in India, this too may be suspect.

1. c.       Cost/COA reduction:

Because of the Indian online behavioral patterns, companies have been relying on content for achieving sales growth. The danger lies in the direct attribution of content to sales. It will come as no surprise to campaign managers that COA on content would be at least thrice of search – shocking the daylights of most product managers. That it is imperative to look at content / display spillover on search – organic and paid & direct website traffic exists at present only in theory. Therefore, in the absence of any satisfactory metric, online display ads have been measured against the COA yardstick. The idea is waste elimination on content or sites that don’t meet benchmark COA targets and spends optimization.

 Most of the above analysis in India is done on a post click basis but it alienates people who may have viewed the ad, retained the information and then at a later stage completed the desired action.

Affiliate marketing’s Post impression cookies and Google’s more recent View through conversions tracking answer those questions.

 Although using post impression tracking may not be free from doubt, it still will be better that using only the click to judge display ad performance. Of the two goals of Sales increase or cost reduction, the latter is more suited to gain from accountable view based metrics like above.

 Here are some thoughts on how to better this:

• Reduce the life of the cookie window to 15 or 30 days. This has to be done in the light of product conversion cycle and the digital medium used – search, content , display.
• Have a common cookie window policy across all digital mediums (display, affiliate networks, search etc.)
• Cookies placed should be a combination of User + domain name + Ad unit – thereby avoiding the possibility of repetitive attribution.
• Cookies should also contain frame details. A frame cookie can place the cookie only when that frame is viewed – thus the view through could be view around conversions.

After much analysis we realized that there were a lot of drop outs before the final lead.  Site’s main page took a lot of time to load. Also customers who were searching for specific jobs like “IT jobs, Java jobs, HR jobs, etc., did not see any these jobs on the landing page. This lead to a huge bounce rate of about 81% on major keywords.

The client wanted reduced CPL with 20% increase in leads and the bounce rate to be improved by 45% – 50%. After analyzing we presented the following bunch of ideas of improved landing page to the client.

1)      Instead of site’s main page, let us direct traffic to a new registration page.

2)      The new landing page will have a short 4 field form with user id, password and email id fields.

3)      Below that will be “Upload CV” tab.

4)      On the right we will place jobs relevant to his searches. These will be dynamically inserted.

5)      On the top right we asked him to place a Job search bar.

We presented these suggestions with a layout design.

The client asked us to go forward with this as a test. The page was set live and the result were just amazing.

The lead price dropped by 50%. Bounce rate came down to 40% and the leads number increased by 25%.

The key learning we got from this exercise are as follows.

1)  Purpose of Job queries were to find the relevant job. We served justice to that on the new landing page itself.

2)  The client’s business objective was to get more CV’s instead of traffic. The upload CV tab just did the same.

General Insurance provider reduces online customer acquisition costs by 30% with help from Communicate 2’s analytics team.

Objective

To differentiate organic search referrals from AdWords referrals, track visitors across unique domains and fully populate all relevant Google Analytics reports. Profiling of back linked sites, gauge which AdWords keywords deliver the best results and make changes to AdWords campaigns to maximize effectiveness and above all to track Cost of Acquisition for all click based campaigns.

The Challenge

Registration & ‘Thank You’ Pages were on a sub domain; hence conversions were not being attributed to the correct source. Duplication of data resulting from populous query string parameters. Ensuring that traffic to the website is of good quality.

Solution

• Cross-domain tracking by customizing the code using the setDomainName() & _setAllowLinker() functions ·
• Exclusion of query string parameters to avoid duplication of data
• Analysis of keywords that have high bounce rates to optimize Search Campaigns
• Funnels setup to investigate how often particular search terms end in conversions
• Analysis of traffic from all sources to gauge specific visitor engagement (bounce rate, time on site,
  navigation path)
• “User-defined” segmentation or eCom integration recommended to track conversions by product category, age,  gender & ROI

Results

• Resolving the sub-domain issue helped in identifying performing keywords from natural search resulting in
  optimized paid campaigns
• Enhanced monitoring of Return on Investment with greater control on Cost per Acquisition ·    Greater efficiency in content targeted campaigns