Visitor Insights

We’re proud to announce the general availability of Tealium Social Media, a new measurement service for social media and online PR that’s tightly integrated into web analytics. The service is designed for marketing professionals who use social media and online PR as marketing vehicles to generate awareness and demand, and require side-by-side comparison with other marketing channels.

For a review of Tealium Social Media, please visit this blog posting by PR measurement guru, KDPaine.

How does it work? Consider this scenario:

A visitor is in the market for CRM software and comes across a blog comparing various CRM programs. The blog mentions a number of CRM applications that the visitor had no previous knowledge of, including SugarCRM and NetSuite. Because of the great feedback in the blog, the visitor decides to go to SugarCRM by doing a search for “sugar crm” on Google. This leads the visitor to sugarcrm.com, where the visitor requests a personal demo.

With traditional web analytics, this conversion would be attributed to Google. With Tealium Social Media, the conversion will also be attributed to the original blog that started everything.

Tealium Social Media is a web analytics plug-in that is integrated into popular web analytics solutions: Google Analytics, SiteCatalyst, Unice NetInsight, WebTrends, Coremetrics, etc. This means you can get your social media ROI measurement directly inside your existing web analytics account.

Intrigued? Request a demo.

PR Measurement, Social Media, Web Analytics, online marketing google analytics, hbx, omniture, online marketing, PR Measurement, sitecatalyst, Social Media, social media measurement, Web Analytics

I was watching the wild card playoff games between the Falcons and Cardinals where I noticed a huge media buy by Hyundai for the Hyundai Assurance program. According to the official press release,”Hyundai is providing a complimentary vehicle return program for the first year on every new Hyundai that is financed or leased for owners who experience an involuntary loss of income within 12 months of the purchase date”.

Certainly this is an unprecedented move in the auto industry. And marketing wise, it is a brilliant one. According to the American Marketing Association, marketing is defined as “the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers”. This program certainly provides value to customers in these economic times.

And after only two days, it looks like the program is so far getting a great deal of coverage through the press, blog community and social networks. Congratulations to the marketing folks at Hyundai for creating a relevant marketing program for the times.

Uncategorized, online marketing online marketing, PR Measurement, Social Media

A while back we published a post on using Google to predict elections. A similar post has recently been submitted by Jeremiah Owyang on the use of social networking stats for similar analysis. Obviously, in both cases, one cannot heavily rely on these numbers to predict elections, as they’re a reflection of interest and one cannot guarantee that interest turns into votes. But in both cases, there’s a great deal of entertainment value associated with the data.

However, a recent article in New York Times reveals a much more powerful side of Google Trends. In this case, Google is using its search data ot track the spread of flu within the United States. More specifically, deta from last year revealed that Google saw a spike in number of searches for terms such as “flu symptoms” about two weeks before the CDC (Centers for Disease Control) reported regional outbreaks. The graph below shows the comparison between the two data sources.

I must admit this is one of the most clever uses of Google Trends as it captures real data in a manner that can be used to actually predict trends. Congratulations to the folks at Google.

SEM, Social Media, Web Analytics, online marketing online marketing, SEM

Google recently announced a major upgrade to Google Analytics. The new version now includes features and functionalities once available to high-end solutions. Among these new features is the Advanced Segments functionality which lets users create complex segments using a drag-and-drop interface. In order to help users get started, Google has already included a number of pre-defined segments such as “New Visitors”, “Returning Visitors”, “Search Traffic”, “Direct Traffic”, etc.

The pre-defined segments should greatly increase user adoption of this functionality. At the same time, users will be able to further extend the value they get from the tool. We’re going to outline some additional segments that can further add value. For this post, we’re going to concentrate on lead generation site types, whose goal is to generate leads for the sales team that are eventually closed off-line.

Note: These segments are also applicable in other web analytics solutions, even though the examples are provided for Google Analytics.

Some quick win segments that you can get started with are:

1. Form Page Visits
2. Form Abandonment Visits
3. Engaged Visits
4. Highest Value Conversions

Form Page Visits: One of the pre-defined segments in Google Analytics is “Visits with Conversion”. As long as you’ve defined your site goals in Google Analytics, this segment will filter out visits where a goal event has occurred. The segment will let you identify your most effective acquisition sources for example. However, you can take Google Analytics to the next level and define a segment based on visits where your site visitors hit the form pages (just before the conversion). Why? People who make it to the form pages are also considered as qualified visitors, even though they don’t fill out the forms. This segment will also let you identify your best acquisition sources, whether a conversion occurs or not. This segment can be created by selecting the dimension “Page” from the “Content” list and typing in the name of your form pages. If you have multiple form pages, you can add them by adding an “or” statement.

Form Abandonment Visits: This segment will filter out visitors that make it to the form pages but do not complete the process. This segment is valuable because it lets you identify where you’re leaving money on the table. This segment will consist of two filters. The first one is similar to that used for the “Form Page Visits” segment. The second filter is using the metric “Total Goal Completions” and setting the value to equal zero. The relationship between the two filters should be an “and” statement.

Engaged Visits: Regardless of whether your visitors convert or hit the form pages or not, you’re still interested in how they consume your content. The “Engaged Visits” segment lets you filter out the site visitor that are engaged in your content. An easy way to do this is to start by your average number of pages views per visit and time on site. You can then build a segment with two filters. The first filter is by selecting the “Pageviews” metric and making sure that it is set to a value greater than your average. The second filter (“and” statement) uses the “Time on Site” metric, as shown in the figure below. You can take also this segment to the next level by adding recency into the equation. Eric Peterson has recently posted about this very topic, and we recommend his approach for media sites. For lead generation sites a simplified engagement approach should suffice.

Highest Value Conversions: Not all web leads are created equal. For companies that offer only one product or service, this may not be an issue. But for many lead generation sites and companies that offer multiple products, this will be of importance. For example, you may have a free and a paid version of your product. In that case, you would be more interested in visits that result in a lead for your higher-end products.

In some cases, this may be an easy segment to build if your conversion pages for your various products are different. Often times, you’re using the same form page to capture leads for all your products. In such cases, we recommend that you allow visitors to choose which products they’re interested in form within the forms and capture the user selection in Google’s User Defined variable. By doing so, you can then build a segment based on the “User Defined Value” dimension under the “Visitors” group. The new segment will then allow you to determine where to target in order to capture leads for your highest value products.

Web Analytics, Web Analytics Reporting, online marketing google analytics, lead generation, segmentation, Web Analytics

We’re all looking forward to the eMetrics conference next week. This is the premier event for everything and anything web analytics and with all the changes happening in the industry, this event is a must.

We’re specifically interested in connecting with other industry experts and see how organizations are tackling their analytics challenges.

If you’re also attending the event, please drop us a note.

SEM, Social Media, Web Analytics, online marketing emetrics, Web Analytics, web analytics conference, web analytics consulting

One of the most popular KPIs for lead generation sites is “Cost per Lead”. It lets marketers know whether they’re spending the right amount on marketing campaigns. However, a better KPI for such customers is “Cost Per Qualified Lead”. It provides a more accurate picture of the campaign performance.

The following is what a customer has recently shared with us regarding their use of WebToCRM.

Note: the numbers have been revised in this post.

After running a number of online campaigns, they were able to use their web analytics solution to determine high-level performance metrics such as campaign clickthroughs, conversion rates and cost per lead. The sample data is shown in the first graph below.

The campaign conversion rates are mostly within the same range. However, because of the higher conversion rates and lower cost per click (CPC), newsletters end up generating a much better cost per lead (CPL). Based on this data, it would make sense to take some budget away from search engines, which have the highest cost per lead and put that money towards more newsletter sponsorships.

However, the customer did not stop there. Thanks to WebToCRM, they integrated their online campaign data into their salesforce.com implementation and decided to break down their leads into two classifications:

• Qualified leads: these are defined as leads with complete and accurate information, including the person’s full contact information, job title and decision making timeline.
• Unqualified leads: these are leads with incomplete or inaccurate information such as fake email addresses, etc.

How do the numbers hold up when you look at qualified leads instead of just the raw number of leads? The picture turned out to be quite different and is shown below.

With a simple “Cost per Lead” KPI model which is what many web analytics practitioners use, the company would have diverted money from search engines into newsletters. However, the more relevant “Cost Per Qualified Lead” KPI shows that the customer would be well served doing the exact opposite. Although search engines provided fewer leads per click than newsletters, they also provided a far higher percentage of qualified leads. The client is therefore going to continue its investment in search engine marketing.

Still wondering about the value of cross-channel analytics? Think it’s expensive? Take another look at WebToCRM. It lets you integrate your online campaign data into your CRM application, regardless of what web analytics or CRM tool you use. Best of all, the Free edition give you the same level of data that you see in this example.

SEM, Web Analytics, online marketing B2B Web Analytics, kpi, lead scoring, online marketing, SEM, Web Analytics

Today’s major search engines let you show your ads both through their search (keyword advertising) and content networks (contextual advertising). One common mistake that we see happening in the industry is that companies run both their search and content advertising the same way: same keywords being targeted, sames ads and same landing pages. By doing so, they also compare their search and content network performance side-by-side and typically see better results through their search network.

Does this mean that you’re better off discontinuing the contextual advertising and putting your budget towards search advertising? Not necessarily. The reality is that these two networks serve very different audiences and with proper strategy, you can leverage them both optimally. We’ve even seen customers who do much better within content network compared to search networks.

In order to explain this, we’re going to look at the customer sales cycle first, which is shown in the figure below. This is a simplified version of the AIDA model (Attention > Interest > Desire > Action).

Within the online world, the sales cycle consists of three key stages:

• Awareness: clearly the first stage is that future customers will have to be aware of you or your company. How can someone do a search for you or your products if they don’t even know your industry or what you do? Awareness is mostly created through channels such as press releases, news sites, blogs and many of the social media outlets.
• Influence: once people are aware of your product or industry then you can influence their sales decision. In the online world, this is done through the traditional online marketing channels such as banner ads, PPC advertising, email and newsletter campaigns.
• Action: this is the step of actually converting. This component can either be an e-commerce transaction, an online lead generation, a newsletter registration or else.

From here, we can now see the different audiences that search and content networks serve. The search network is serving those who are doing an actual search. That means that they’re already aware of the industry or the product and as a result, search generates high click-through numbers and high ROI.

The content network on the other hand has to be treated differently. You cannot assume that those who see your contextual ads are already aware of your products and you will very likely see much lower click-through numbers within content networks. So for many companies with complex sales they’ll be well served to use content networks as a venue to generate or increase awareness. We’ve even seen companies serving new industries that have seen much better performance on contextual advertising. This is because they’ve been able to leverage the content networks to increase customer awareness about their products.

This also means that you cannot rely on click-through and conversion rates to compare your search and content network performance. Instead, you’ll have to look at the effect of your content network at increasing your search click-through and ROI.

SEM, online marketing contextual advertising, search advertising, SEM

Ever tried measuring the return on investment of your press releases? Although seemingly simple, the process turns out to be more complex than one might think.

Recently we published a press release announcing the WebToCRM product. For those of you interested, it can be found here.

The purpose of the press release was to introduce WebToCRM, but also to generate traffic and leads to the tealium.com Web site. So how did the press release do? It turned out to be quite successful as shown in the chart below. It ended up generating a tremendous boost in traffic.

The site traffic on May 20 increased exponentially on the day of the PR launch. Given the fact that Tealium is a startup and the site does not get much traffic today, clearly the increase can be attributed to the press release.

But drilling down into the data reveals a hidden value of PR that cannot be detected by web analytics solutions. To analyze this more, we’ve broken down the traffic by source. The categories analyzed are “Bookmarks or Directly Referred” (typically direct traffic to the site or emails), “Search Engines”, “PR Sources” (compilation of referring URLs associated with the news stories), and others (not fitting any of these mentioned categories). The results are shown in the figure below.

We’re analyzing two seven-day periods, one before the release and the other after the release. The results are definitely revealing. Obviously, the PR traffic increased since there was no PR the previous week. But more interesting is the fact that both the bookmark and search engine traffic increased dramatically as well. In other words, there’s a hidden value to PR that previously hasn’t been mentioned in the Web analytics world. Because of the press release, more people came to the site directly and more people searched for “Tealium” on search engines.

If you’re a marketing veteran, the results make sense. Press releases are a great medium for generating awareness. Also, by creating a marketing mix that includes multiple touch points (PR, search, banners, trade shows, etc.), you’ll get an overall result that exceeds each one of the touch points combined. In other words, 1+1+1=4.

However, it also reveals the challenges associated with PR measurement. It shows both the effectiveness of online PR, as well as the difficulty of measuring it. In our case, this was not a difficult task, because of the reasonably low traffic that we were getting before the press release. But if you’re a high traffic site, measuring the effectiveness of PR becomes much more challenging and certainly an area that has not been addressed by Web analytics solutions.

The field of PR measurement today consists of understanding your Outputs, Outtakes and Outcomes. Outputs and Outtakes are fairly simply to measure, but Outcomes (the business results of the PR – site visits and conversions in the online world) are much harder to measure, and ironically more valuable. We’d love to hear back from you about your experiences in this field and what you’ve done in your organizations to solve this problem.

PR Measurement, Web Analytics, online marketing marketing mix, online marketing, PR Measurement, Web Analytics

An unscientific approach!!!

One of my favorite tools to see trends, patterns and seasonality associated with search terms is Google Trends. It lets you see trends associated with specific keywords and compare up to 5 keywords together.

With all the buzz around the democratic primaries, it was only fitting to use Google Trends to see if we could see patterns that could shed some light into the outcome. The results, although not scientific are pretty revealing. First off, here’s a comparison of searches for the terms “barack obama” and “hillary clinton” over the last 12 months. We’ve obviously filtered out the international traffic and the results are shown in the figure below.

The interesting trend here is that Obama was behind Clinton in terms of searches till January of 2008. January 3rd happened to be the date of the Iowa caucuses which showed a surprising win by Obama and one can speculate put him on the map as far as the general audience is concerned. To test the hypothesis, lets look at a similar comparison, but this time between “huckabee” and “mccain” and interestingly, we see a similar pattern.

Within the GOP front, we see a spike in interest for Huckabee prior to the Iowa caucuses and a decrease after McCain gains momentum from consequent wins.

How accurate is this?

So you’re wondering, how accurate is this? While Google Trends is a great tool for search engine marketing, it is simply not built to forecast elections and markets. For example, if you look at the breakdown by states, you can see that the term “barack obama” gets higher traffic than “hillary clinton” in all states, including Pennsylvania, Kentucky and Ohio – where Hillary Clinton won by a large margin. This is shown in the image below.

In fact, in terms of popular vote, both candidates were neck and neck. And you can make the argument that most people did not know much about Obama before the primaries began and therefore what we’re seeing is people educating themselves about the candidates. But it’s certainly fun to see the trends in terms of peaks and valleys around some specific events such as the start of primaries and caucuses.

The purpose of this post is not to endorse any one candidate or make market predictions, but rather showcase what you can get from Google Trends. The information can be very useful in determining peaks and valleys in user interest associated with specific events of relevance to your business.

SEM, online marketing 2008 election, barack obama, hillary clinton, online marketing, SEM

The Tealium team is proud to bring closed loop marketing to the masses. Once an undertaking feasible only to large organizations with deep IT investments, WebToCRM lets you integrate your online marketing and web behavior data into your CRM solution – for free. That’s right: free.

WebToCRM works independent of your web analytics or CRM platforms and requires no integration between solutions. It is a JavaScript based solution that lets you push your online campaign parameters into your CRM solution in real time.

WebToCRM comes in three editions:

• The Free Edition lets you capture your online marketing campaign parameters (up to four) and pass them to your CRM or internal database once a lead capture event occurs.
• The Plus Edition provides what’s available in the Free Edition, plus session referrer, page view and time spent during session (aka engagement metrics) upon the lead capture event.
• Finally, the Custom Edition lets you capture custom data points that you can use within your CRM solution for lead scoring purposes.

WebToCRM is completely independent of your web analytics platform: Google Analytics, IndexTools, MS Gatineau, Omniture, Coremetrics, WebTrends, Unica, Xiti or any other provider.
Additionally, it can pass the data collected into any CRM solution including Salesforce, SugarCRM, NetSuite or your own internal databases.

We will be posting additional posts soon on uses and best practices associated with the WebToCRM solution. In the meantime, feel free to configure and download your free version of WebToCRM. What do you have to lose?

Web Analytics, Web Analytics Implementation, online marketing b2b, closed loop marketing, crm integration, Web Analytics