I’ve found six reports for Twitter client statistics from Many Eyes/IBM, TwitStat, Sysomos, Twalytics, Funkatron, and TweetStats, however there are some big differences among their reports. For example, web (twitter.com) usage varies from 18.9% to 48%; TweetDeck varies from 6.6% to 13.8%; and Hootsuite varies from 0.6% to 5.2%. That’s a lot of variation considering these reports were all generated on the same day (Feb 5, 2010) with the exception of the Sysomos report (Nov 16, 2009). Averaging the results among all six reports reduces the variances likely due to the different data collection methodologies.

When we average the results we can see that 38.1% of all Twitter activity takes place on twitter.com (Web), and 2.4% takes place on m.twitter.com (mobile web), for a total of 40.5% of twitter activity coming from the twitter.com domain. Why does this matter? Marketers need to be able to measure the volume and quality of traffic coming from Twitter to determine an ROI for their efforts. If you’re only measuring visits from twitter.com in your web analytics tool, you’re only measuring 40% of all the activity.

Here are three possible solutions…

1. Trackable URL shortening services

Services like bit.ly, cli.gs, tr.im, and HootSuite’s ow.ly will provide statistics on how many clicks were generated from your twitter posts. This is especially useful if you just want the number of clicks, but any good analyst knows that it’s what happens after the click that really matters. These services cannot measure any of the activity that happens on your website post-click, so using URL shortening services alone can only provide limited insights.

2. Append tracking codes to all links posted on Twitter

Most web analytics tools, like Google Analytics, allow you to append tracking parameters to links in order to report certain visits under a specific campaign rather than direct traffic. Links posted to Twitter are perfect opportunities for tracking codes since around 60% of your Twitter traffic could potentially be reported as direct visits. If you use Google Analytics, Google offers a free tool to help you add these parameters to your links.

So instead of posting your link as:
http://www.mydomain.com/abc

You could use this link instead, with added Google Analytics tracking paramters:
http://www.mydomain.com/abc?utm_source=twitter-feed&utm_medium=social-media&utm_campaign=twitter-abc

These parameters can make links really long, so you’ll need to use a URL shortener to post them on Twitter. When you add tracking parameters to all links you tweet, you can start to measure the actionable fun stuff like goal conversions, time on site, visitor loyalty, visitor recency, and bounce rate for all traffic from Twitter, rather than just 40% of it. This information can be a starting point for generating an ROI on your social media efforts.

If you give utm_source a value different than “twitter.com”, you can be sure that all visits from “twitter.com” originated from links posted by tweeters other than you (a good thing!). Comparing your own efforts (traffic from the twitter-feed campaign) to your fans’ efforts (traffic from twitter.com) can yield some pretty neat insights. This can be a good way to gauge how energized the twittersphere is about your brand. To get the most accurate view possible, I’d recommend using a multiplier to estimate the total number of visits from twitter.com (details below)

3. Use a multiplier to compensate for visits from Twitter clients

Since 59.5% of all Twitter traffic could be reported in your web analytics tool under direct visits, a quick (and dirty) way to estimate the number of visits you’re really getting from Twitter is to multiply the number of twitter.com visits by 2.47 (which is 100%/40.5%). This calculation assumes that your audience’s twitter client usage matches that of the overall Twitter population (40.5% use the website), and that the audiences among different clients are uniform (TweetDeck’s users behave exactly like UberTwitter’s). Of course, this is likely not the case, but the more traffic you receive from Twitter, the closer this estimate will be.

Using tracking parameters is definitely the better way to go for accurate & insightful Twitter stats, but the multiplier is a good starting point. And as explained above, tracking parameters can’t be appended to links that are posted by your fans, so applying a multiplier is necessary to estimate the total number of visits generated by all tweeters other than you.

No related posts.

These “best practices” aren’t just limited to calls to action, although CTA’s are notorious for having so-called best practices. Other elements which are subject to the tyranny of best practices are: colours, fonts, size of icons/design elements, advertising, navigation, general layout, style of writing, type of visuals used, design style, and everything else under the sun.

So, how do you determine what’s best for your site? Here are some paths to enlightenment…

Usability Testing

Usability concerns should be the first issues to be addressed – think of it as the low-hanging fruit of conversion optimization. If any element of the site is inhibiting visitors from converting, it should become apparent through usability testing. For example, during the design phase of a relaunch, you can present two versions of mockups to the subject of a usability test: one that uses Add to Cart, and one that uses Place in Shopping Bag, and see if the subject can successful complete the task in either scenario with as little friction as possible. This is obviously an overly-simplified example, but if the subject is confused by any of the variations, you’ll know to completely eliminate the potential for using it. If both are easily understood, it’s up to multivariate testing to determine which one actually converts better.

Multivariate Testing & A/B Testing

Once you’ve addressed all usability concerns, you can start testing different hypotheses through multivariate testing. The key to multivariate testing is to start with a hypothesis – one that is well-thought out. Don’t be afraid to test radical changes – we’re going for big wins here! With multivariate and A/B testing, you can say with confidence that “our tests conclude that on our website, Add to Cart converted 20% more orders than Buy Now, so we should use Add to Cart.” But that doesn’t mean that Add to Cart is a universal best practice because what works for you, might not work for another site. Furthermore, you don’t know if Add to Cart is actually the best converting CTA for your own website – all you know is that it’s better than Buy Now. It’s impossible to ever know what’s “best” because you cannot possibly test every scenario.

Multivariate & A/B testing can be done very easily for free using Google Website Optimizer, however there are several situations where you’ll run into trouble with multivariate testing & A/B testing, so if multivariate & A/B testing isn’t an option for conducting your test, sequential testing is the next best thing, as long as you understand the limitations.

Sequential Testing

Sequential testing attempts to measure the impact of a web design change by comparing the your analytics data for the period before the change to the period after the change. For example, your web analytics tool tells you that conversion rate before June 1 was 2% when you use the Buy Now CTA. On June 1, you change that CTA to Add to Cart. After enough data has been collected, you see that after June 1, your conversion rate is 3%. While it does have its obvious limitations, it can be used instead of multivariate testing so long as you’re careful and follow these guidelines:

• You select time periods where the amount of traffic is relatively the same
• You select time periods where your traffic mix is relatively the same
• Rather than comparing all traffic in aggregate, segment your traffic as much as possible and compare within segments
• Do not introduce any new changes, tools, features, irregular content, or anything else that could potentially influence the outcome you’re measuring
• You gather enough data to have statistically significant results (use the Google Website Optimizer calculator)
• You only conclude the design change has had an effect if you notice a big impact

It’s important to keep in mind that Sequential testing is suboptimal for a few reasons:

• Your traffic sources are naturally going to change from day to day, week to week, and month to month, so it will likely be different audiences seeing each variation
• You must observe a large improvement to conclude there was a statistically significant effect
• You can only test a small number of variations (depending on your traffic level)
• For big websites, it’s almost impossible to leave the site untouched for an extended period of time, so there could be other content/design changes that are influencing the test

But if this is the only method available to you, and you are careful with implementation, it can provide some insight – it’s better than not testing at all.

Surveys

Analyzing clickstream data can show you what is happening on your site, but qualitative data such as surveys will help you answer the “why”. Surveys can answer questions that your data cannot, giving you further insight into exactly what works and what doesn’t on your site. Survey answers can give you great ideas for testing. For example, you could ask your paying customers what factors affected their purchase decision. If there are any surprises, it would certainly be an opportunity for testing.

Continual Testing

Audiences change over time. What works for your site today might not work for your site next year. It’s important to keep testing new and old hypotheses to make sure you’re always using the most effective tactics for your current audience. Amazon is famous for this. At any given time, they’re running several multivariate tests, which is one of the reasons they’ve been able to consistently generate unheard-of conversion rates of over 15%. Amazon has embraced the fact that best practices don’t exist in web design, and so should we all.

No related posts.

1. More effectively evaluate your traffic sources

You have likely defined a couple goals which are crucial to your success such as submitting a lead generation form, or buying a product. You likely also have some other secondary goals which you want to track, but are not as important in the grand scheme of things, such as posting a comment or entering a contest. If you do not define goal values for each goal, the only way you can get a holistic view of which traffic sources perform the best is by using the average conversion rate for all goals which essentially treats all goals equally. By assigning goal values, you can adjust the weighting for each goal. Submitting a lead generation form could be worth $100.00 to your business whereas submitting a comment could be worth $1.00. When you make this distinction, you can see that while traffic source A has a lower average conversion rate than traffic source B, visitors from traffic source A are more likely to submit the lead generation form (worth 100 times more to your business).

This might seem trivial in this example, but if you are utilizing goal tracking as effectively as possible, you should have at least 5 goals set up. With this many goals, you NEED to use per visit goal value to truly see how valuable the traffic source is to you.

2. Easily determine ROI on your Pay Per Click campaigns

As mentioned in #2 above, if you’re not assigning goal values, you are evaluating traffic sources on average conversion rate, thus treating all goals equally. With PPC campaigns, goal values become even more important because they can tell you if you are losing money or making money on a specific campaign. If you are using Google Analytics and Adwords, your PPC campaigns are already integrated to your web analytics software – nice! If you’re using another set up, there are likely some steps you’ll need to take so that your PPC campaigns are integrated with your web analytics software. Comparing RPC and CPC, your web analytics package can compute the ROI and Margin – essential information for determining how to best optimize your PPC spending. You could be spending $100 a month on a PPC campaign that has a low average conversion rate, but high RPC and speding $10,000 per month on a PPC campaign that has a high average conversion rate, but low RPC, and you wouldn’t know unless you actually assign goal values.

3. Use “$ index” to choose which pages to optimize

Many web analytics packages will calculate a metric for each page on the site called “$ Index” or “dollar index”. Calculation of this metric is slightly complicated, but analyticsmarket.com did a great job of explaining it:

[$ Index is...] A measurement of how influential a page is to conversion. It doesn’t indicate how much money a page brought. Rather, it’s a score. The higher the number, the more frequently it was viewed prior to a purchase or conversion. It’s calculated by taking the goal conversion value or transaction value of a visit and applying it evenly to all the pages prior to that conversion. Seen in aggregate, it just attempts to correlate pages to conversions.

So, the more important a page is to a goal conversion, the higher the $ index. And, the more important a page is to a high value goal conversion, the higher the $ index, because all goals are not equal. If you do not assign goal values, $ index for every page will be $0.00.

In your top content reports, you can see the $ index for each page on your site. You may find a few surprises of your top landing pages that have exceptionally high or low $ index values – take a look at these pages to see if you can learn anything from them. Is there anything we can learn from the high $ index pages, and apply to the low $ index pages? Do you have any hypotheses you’d like to test with a multivariate test? $ index is a great metric for deciding where you want to focus your optimization efforts.

4. You will never have complete information, so just jump in now

If you have been putting off assigning goal values because you don’t have all the necessary information, do not let this hold you back – you could be missing out on key actionable insights. Gather whatever information you can find to help you determine the value of one conversion for the specific goal, and assign the value to that goal. In web analytics, it’s very rare that you will have every piece of information you need, so just do your best with the information you have. You can always change it down the road (although only future goal conversions will use the new goal value after the change).

The most important consideration when assigning goal values is not the absolute value of each goal, but the relative values. In other words, if submitting a lead generation form is 100 times more valuable to your business than posting a comment, make sure the lead generation form goal value is 100 times the goal value for comment posting. Try to get the goal values as accurate as possible, but in most cases, it’s impossible to have perfect information, so just do your best.

5. Show your boss/investors/CEO the dollar value of the website

You could go to your CEO and say “Our website had 413 newsletter signups, 285 comments, 14 lead generation form submissions, 1030 social shares, 79 RSS subscriptions, and 306 account registrations last month,” to which she will probably reply, “Great – so what?”

When you can speak to your CEO in a language she understands (dollars and cents), you will get a better reaction, and get your point heard. What if you said “Our website had 413 newsletter signups, 285 comments, 14 lead generation form submissions, 1030 social shares, 79 RSS subscriptions, and 306 account registrations last month, representing $42,864 in value to our business, up $8,477 month-over-month.” This clearly communicates the value the website brings to the company, and you’re much more likely to receive the support you need.

No related posts.