Digital is a channel that can and should be tracked end to end – data capture starts from an impression and goes all the way to the final sale. As a company specializing in Search and Social Media, we regularly educate our clients on the importance of granular tracking and help them improve their existing tracking methods across platforms. With integrated in-house PPC, SEO and Analytics teams, we constantly seek to maximize our client’s campaign ROI through regular research, granular data capture and analytics.

This article’s focus is to showcase the importance of capturing paid search (PPC) keyword data through analytics. Google Analytics (GA) has been considered for this discussion. While you might have a different analytics tool, we believe that the information here still applies to your PPC campaigns and you should try and get similar data from your current analytics system.

Capturing Keyword Data through Google Analytics

When it comes to PPC, it is important to capture all the metrics accurately within the main user interface (Google Adwords) and the analytics system (GA). The metrics captured can be categorized as ‘front-end’ and ‘post-click’.

Front-end metrics cover data on keywords, ads and the landing or destination pages, and include clicks, Click through Rates (CTR), Conversions/Leads, sale value, Cost per Lead (CPL) etc. Post-click metrics include bounce rates, average time spent on site, % of new visitors and much more.

Adwords provides keyword information up to the point where the user clicks onto the website or the landing page. Post-click performance on GA shows user behavior on the destination page or the website. This information helps understand if users landing on the page stayed on it, if so, for how long, how many pages they visited etc.

Keyword level data can be obtained from GA in multiple ways. Keywords can be analyzed individually or at an aggregate level by defining segments. Data for one of Position²’s client in the B2B space is shown below as an example. An advanced segment named ‘Brand’ keyword aggregates data for a pre-defined set of corporate and brand name keywords. Similarly, the ‘Non-brand’ keyword segment excludes traffic from these keywords.

Table 1.0: Aggregate Branded VS. Non-Branded Keywords


Table 1.1: Keyword Level Performance

Regardless of the business type (B2B, E-Commerce etc), capturing keywords through analytics is crucial. Some of the key advantages of having keyword information through GA are provided below. The benefits should typically apply to any analytics platform you may be using.

• Keywords within GA help determine the performance at an aggregate level. In Table 1.0, aggregated performance of brand Keywords shows that they are producing 100% bounce rate and no conversions; an unusual occurrence for brand terms. This information indicates that the users landing on the destination page(s) are not finding what they are looking for. By extracting this data from our client’s GA account, we understood that those conducting branded searches could be doing so to sign-in to their online accounts. If the campaign objective is lead generation or form fills, the campaign may be better off without these specific terms.
• GA can be used to determine if non-performing keywords should be weeded out of the campaign or if new messaging should be tested. In Table 1.1 Keyword 5 and Keyword 6 are poor performers. These terms have 100% bounce rate despite driving new users and a reasonable time spent. For these keywords, it would be important to evaluate the ad messaging and the landing page copy.
• Keyword data from paid search can be compared with numbers Organic traffic. For example, if there is a drop in traffic and leads for a keyword in paid search, Organic traffic for the same keyword can be compared to check if it’s a seasonal trend.
• Destination URL performance can be evaluated down to a keyword level. This helps identify the best combination of Keyword-Destination Page and crucial information for campaign optimization.
• Performance for each keyword and post-click activity can be obtained in every match type (Exact, Broad and Phrase). Precise user queries that triggered the ads and their post-click performance can also be gathered. Again, important data for campaign optimization.
• The best position for keywords can be determined. As seen below, the position and post click performance for keywords can be captured. Crucial data to make decisions on keyword positions.

  

Passing the Keyword Data within GA

You can pass paid search keyword data to GA by:

1. Adding UTM parameters to destination URLs or
2. Linking the GA and AdWords accounts and enabling Auto-tagging in Adwords

Let’s now examine how you can pass keyword data to other analytics platforms.

AdWords ValueTrack allows passing detailed data to any tracking system to optimize campaigns. By adding parameters to the destination URL, it is possible to pass information on keyword, ads etc.

Here’s an example -

Destination URL tagged with parameters for keyword and match type:

http://www.example.com/?keyword={keyword}&matchtype={matchtype}

Actual URL post visitor click

http://www.example.com/?keyword=used%20cars&matchtype=p

Your tracking system will need to parse these parameters and allow for slicing and dicing of data based on these.

We recommend doing exhaustive testing to ensure all required information is captured accurately on your platform.

Conclusion

Keyword data helps optimize paid search campaigns down to the most granular level possible. This will in turn help generate efficient (low Cost per Lead) and quality leads. It will also provide multiple testing opportunities with messaging, positions and landing pages.

Not having keyword tracking within analytics will still allow for campaign management, but at an aggregate (ad group) level only. While not the optimal way to manage paid search campaigns, this will still help in optimizing campaigns possibly to increase leads.

At Position² we encourage all our clients and work closely with them to take advantage of granular information through their analytics platform. We use end-to-end performance metrics to optimize campaigns and work with our clients to improve not only the PPC performance, but also Analytics set-up, SEO performance and their sales process.

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Segmentation is a feature offered by many web analytics tools. It allows grouping of website visitors based on certain common characteristics. Some examples of segments are:

• Visitors coming from paid search campaigns
• Visitors spending more than ‘x’ minutes on the site
• Visitors who download a product brochure, etc.

Segmentation leads to deeper insights about our web site visitors. In the words of Avinash Kaushik it helps us in becoming Analytics Ninjas!

The Position² Analytics Team segmented website traffic for one of our clients based on certain pre-defined criteria. This client offers privacy and security certification and compliance services for websites. Here is what we found:

Problem Statement

The client’s website was receiving a very high number of visits but their conversion numbers were extremely low.

Analysis

We started by defining a conversion on the site. To count as a conversion (lead), a visitor needs to sign up to ‘know more’ about the services provided. Rather than just looking at the aggregate traffic we segmented it as follows:

1. Visits by Source (Referring Sites were sending 81% of the traffic)
2. Conversions by Source (Paid Search traffic was the major contributor with 95% conversions)

We followed it up with a segmentation of visits by intent, using the ‘advanced segmentation’ feature of Google Analytics, and discovered that all referral visits can be classified into three C’s

1. Credential Verifying Visits: Verifying member site credentials.
2. Complaint Visits: Complaints about member sites regarding privacy violations
3. Content Visits: Visits related to site content

Visitors under categories 1 and 2 visited pages containing specific keywords in the URL (which were not present in URLs of other pages). This fact was used while creating the ‘advanced segments.’

We compared these segments on the basis of their ‘content engagement metrics:’

• Average Time on Site
• Pages Per Visit
• Website Bounce Rate
• Percentage of Returning Visitors

From this graph, it is clear that ‘Credential Verifying Visits’ fared poorly on all metrics as compared to ‘Content’ and ‘Complaint’ visits:

Inferences

• Referring Sites bring in 81% of the traffic, but these visitors do not convert, as they mostly visit to
• Verify the credentials of other sites
• File a privacy violation complaint
• More than 95% of conversions came from PPC campaigns, which account for just 0.2% of total traffic.

Based on these findings, the client immediately saw the value of increasing their spend on PPC campaigns as that is where they got the most conversions from.

Segmentation based on user intent helps you drill deeper into where your most important traffic comes from, enabling you to focus your efforts on the traffic that matters the most to you.

Contributed by Ravi Shukla, Analytics Team

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All products have a demand cycle of their own. Understanding this becomes important when making marketing decisions. Sales reports may give marketing teams plenty of data on seasonality and demand trends, but they may miss out on an important KPI in the online context – the amount of interaction a visitor has with a site before converting.

The way customers interact with a site is very complex. A visitor might search for a product, click on a PPC ad, enter your site, visit your competitor’s site, then come back to compare prices, postpone decision making, and come back after two weeks to complete the purchase.

At Position², we call this the Holy Grail of Web Analytics.

Google Analytics provides two metrics as part of their Ecommerce Reports – the ‘Days to Purchase’ and ‘Visits to Purchase’ reports. These pan-session metrics tell us how many visits have occurred (and days elapsed) since someone’s first visit, until a purchase action took place. You can get a good understanding of your customers’ behavior by analyzing these reports.

A Closer Look

To illustrate, let’s look at one of our clients in the manufacturing sector.

    

Less than half of the purchases occurred on the same day as the first visit, and almost 38% of them took place after 5 visits or more. This suggests a long sales cycle with multiple interactions with the site before conversion.

While this in itself is good to know, it is not actionable. What a marketer really needs to know is which customers convert on Day 1 and which ones need more handholding and cajoling before they convert.

The Next Step

We segmented the above data and looked at time to convert across different acquisition sources.

A look at ‘Days to Purchase’ data across sources shows that the site average has been influenced by ‘Direct’ visitors. More than 70% of PPC visitors converted with 48 hours, indicating a strong PPC strategy that targeted the right audience with the right communication. Direct visitors usually take the longest time to convert, whether they are existing customers or visitors from offline campaigns.

In contrast, the ‘Visits to Purchase’ data for PPC does not look as advantageous. Almost 44% of purchases ocurred after 3 or more visits. This could imply a not-so-attractive offer, or a Landing Page (LP) that does not work very positively with visitors. The numbers stack up very well, though, for Organic visitors, with 65% of sales occurring over 1 or 2 visits.

Delving Deeper

We went on and broke down the search visitors by keyword type to see if there was a difference in behavior for brand keyword visitors.

As expected, the brand keyword visitors converted much faster. The next logical step was to segment data by visitor source.
Interestingly, the Non-Brand visitors for both PPC and Organic took a longer time to convert, with one-third of Non-Brand PPC visitors requiring more than 9 visits to convert. One promising solution was to analyze the ‘Top Content’ of this set and design a separate landing page that addressed them better. Ideally, we would test this new LP against the existing one to compare their performance. Another possible recommendation would be to capture the visitor’s email ID in a form and send reminder emailers or enticing offers.

Conclusion

The above analysis reveals a cycle of first time visitors entering the site through PPC non-brand keywords and returning several times before converting. Since these visitors know the brand name from multiple visits, they use organic search (Segment-organic return visitor using brand keywords), or type the URL directly into the browser (Segment- PPC return visitor using brand keywords, or Direct visitor if the campaign cookie is deleted), to make the purchase.

This knowledge gets us closer to the Holy Grail in terms of better understanding our customers, and significantly provides us with actionable information to help win them over.

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Position² is delighted to announce the launch of a one-time free Google Analytics Implementation Audit Package. The audit evaluates the current Google Analytics set up for a corporate website and provides a score. Apart from the score, companies will also receive a report with recommendations on how to improve their analytics setup. This includes fixes involving advanced configurations.

Speaking about this package, Divya Krishnan, Manager Analytics Group at Position² said, “The need to launch such a package was felt when we realized that every one of our clients for online marketing services needed initial help in setting up Google Analytics either afresh, or in the form of tweaks to ensure data was being collected accurately. This is key for a company to measure ROI on all online marketing initiatives. While Google Analytics is free and easy to install – one needs to get expert help to really leverage it to the fullest.”

According to Vinod Nambiar, Head of Global Delivery at Position², “Our team works across platforms like Google Analytics, Webtrends, Omniture, and Clicktracks. They are well versed with the latest techniques and contribute regularly through articles in this space. Web analytics is a key service that is part of our Marketing Services offering which also include creative production, search and media.”

The Google Analytics audit covers code accuracy, multi-domain and sub domain tracking, tracking events and virtual pages and other custom implementations including ecommerce tracking. This service is being launched for a limited time and will be free for the first 25 requests till December 31, 2010.

To apply, fill up the request form here.

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