Archive

Posts Tagged ‘conversion rates’

Finding Motivation: Why Did They Visit?

January 13th, 2009

In my post, A Model to Improve Traffic Conversion, I refer to four questions that must be answered to effectively recommend and prioritize changes that improve conversion rates. In this post, I explain why it’s so important to understand, “Why did they come?” Analyzing a visitor’s motivation, their intent or purpose, provides meaningful insight as to whether you are driving the right kind of traffic to your site. In capturing motivation, we are also able to create visitor segmentation groups – allowing us to study each group separately.

Model Attributes

Answers Question: Why did they come?
Type of Data:
Qualitative Data
Intent or Result:
Intent

Qualitative Data

Determining motivation, or intent, involves qualitative data. Before getting into the mechanics of capturing this information from the visitor, let’s briefly review the difference between qualitative and quantitative data.

Qualitative data is subjective.  It deals with descriptions that can be observed. In contrast, quantitative data deals with numbers and can be measured.

If you ask a visitor an open question, “Why did you visit us today?” you are asking for qualitative data. By asking the same questions and providing a few “common” answers in addition to a free-form text box, you essentially provide a way to measure “motivation”. The answer is qualitative. Because we can measure it, we can approximate quantitative data from qualitative data.

Make sense? Don’t worry if it doesn’t. All that matters is that by asking visitors to disclose their intent, you are capturing information which can then be used as metrics that can be studied with the rest of your data.

What are the Benefits to Capturing Motivation?

The ability to assess traffic quality and the ability to segment visitors are the key benefits of capturing motivation.

Traffic Quality

It’s not enough to drive traffic to your site. In Analyzing Traffic Sources, I describe how to collect basic web analytics and how the data can be analyzed to measure a source’s rate of success in meeting the site or business goals.

But what about the goals of your visitors?

People come to your site for a reason. When that reason is in alignment with your site’s goals, you’re golden and can move on to increasing satisfaction. When the two aren’t aligned, the first question you should ask is, “Am I driving the right people to my site?”

Establishing intent offers a first glimpse as to whether that visitor will be successful on your site.

As a crude example, let’s say the purpose of your site is to sell photography equipment and film. So you set up a PPC campaign, bidding on the phrase “buy film online” and title your ad “Buy Film Online”. The campaign is generating a high volume of traffic, but you haven’t seen an increase in sales. By analyzing the intent of your visitors from this campaign, you can easily understand the reason for this:

  • 2% visited to purchase film
  • 1% visited to research the price on film
  • 97% visited for another reason

When looking at the “other” information, you can see that the primary reason for visits from this source is to buy movies and films.

Most savy search engine marketers would have been able to tell you this without analyzing intent that “buy film online” wouldn’t yield desired results for a company that sells film for photography. But this illustrates my point that getting the right traffic to your site matters. Capturing motivation from your traffic is a way to measure whether the goals of the visitor and site are aligned.

Segmenting Visitors by Goal

On which visitor would you focus when making site usability recommendations to increase ROI?

Visitor A: The user that came to your site to purchase a tripod, but did not make a purchase.

OR

Visitor B: The user that came to your site to learn more about career opportunities, but did not make a purchase.

While the business or site goal remains the same, the visitor’s intention differs. So does it make sense to group the experience of those looking for career opportunites with those visiting your site to make a purchase? By identifying intent, you can segment users that visit with the explicit intention of purchasing and evaluate their user experience through the purchase flow. With this information you can more accurately make recommendations to improve the site’s usability for those visitors coming to make a purchase.

(Occam’s Razor by Avinash Kaushik has a great video of his discussion with the founders of ClickTracks on the topic of  segmentation at http://www.kaushik.net/avinash/2009/01/actionable-web-analytics-tips.html.)

Best Practices for Collecting Motivation

A simple window can be used to collect information about the user’s intent and motivation when visiting your site. The following best practices should be used when implementing a solution to gather this type of information.

1. Instill confidence.

Instill confidence by refraining from asking for demographic or personal information.  Most people have fallen prey (on and offline) to short surveys that inevitably take up more time than they’re willing to give up.  Make it clear through messaging that you are asking to help their experience.

To help improve your experience on {site name}, please tell us your primary reason for visiting us today.

2.  Keep the options simple

Some or all of the options you present will become system goals.  This way, you can determine the rate of visitors completing their intended goals.  But keep them simple and don’t make them think too hard. You want the visitor to answer the question, not skip it. For example:

The reason for my visit is to:

  • Make a purchase
  • Research a product
  • Learn more about {company} and it’s products/services
  • Other

3. Respect the experience

Be sure to add the ability to opt out of seeing the message again. If they do not opt out, throttle the message so they do not see this message each time the arrive on the site. For example, set the message to display 1 out of every 5 visits and/or 30 days.

You may also want to delay the display of the window.  I like to set mine to display only after 5 seconds or when the user navigates to the subsequent page.  This way the visitor has an opportunity to consume the page’s content before the intent request is made.

4. Make it optional

Don’t require that the user answer the question.  Make it optional.

5. Make it easy to answer the question

Make it easy for your users to answer the question. One way I’ve done this is by stylizing the options as buttons.  This way, it’s evident to the user that they only need to click once to answer the question.

In contrast, I would require slightly more effort to opt out and close.  By including a check box and a button, you make opting out a two click process.  By strategically placing a downplayed close link in a more difficult to reach location (e.g. bottom left of the window), you also add a bit more effort in finding the close button.  Not much, but enough.

Here’s an example of an overlay optimized for gathering intent.

Sample window optimized for gathering intent

Sample window optimized for gathering intent

Summary

Motivation is one of four key components in understanding the 360 degree view of your visitors. By capturing and analyzing visitor motivation you are armed with the information needed to make recommendations to improve traffic quality. Further, by asking a user to identify intent, you can segment groups to study to more effectively recommend site usability improvements based on that particular group’s experience.

A Model to Improve Traffic Conversion, Internet Marketing, Software Product Management, User Experience, Web Analytics , , , , , , , , , , , , , ,

Analyzing Traffic Sources: Where are your visitors coming from?

January 10th, 2009

In my post, A Model to Improve Traffic Conversion, I refer to four questions that must be answered to effectively recommend and prioritize changes that improve conversion rates. In this post, I go into depth about how to analyze your traffic sources.

Model Attributes

Dimension: Source
Question:
Where did they come from?
Type of Data:
Quantitative
Intent or Result:
Intent

Why It’s Important

Collecting data for basic web analytics like referrers or sources provides visibility into how a visitor came upon your site.  While this is a key metric, it does not offer any insight into the effectiveness of those sources.

For example, say you’re a mortgage broker using PPC as your primary marketing effort and banner advertising as your secondary.  80% of your monthly budget is allocated to PPC while only 20% is allocated to banner ads - and your traffic shows it.  10,000 visits a month to your site as a result of the PPC campaigns, but only 200 from your banner ads.  If you stopped your analysis there, your takeaway would be that your PPC campaigns were performing well and meeting your goals.

However, let’s look further.  You’ve established a primary goal - completion of a form to contact you for more information.  A total of 100 visitors complete the form - 10 from your PPC campaigns and 90 from your banner ads.  It’s a completely different picture.  A picture that may lead you to shift more of your budget to banner ads!

Remember… It’s not enough to know how they are getting to your site.  Instead,  it is an important dimension to track as part of the 360 degree view of your visitors.

Web Analytics

From Wikipedia:

Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web site usage.

Several free and inexpensive tools are available and are listed at the end of the post.

Web analytics provides the quantitative data you need to understand where your users are coming from.

Standardized Web Analytics Definitions

I always favor standardization.  The Web Analytics Association released a draft on  Web Analytics Definitions for public comment.  The following is a summary of the WAA  standardized definitions as they relate to this post.

Referrer

Referrer is a generic term that describes the source of traffic to a page or visit and are often collected into meaningful groups to facilitate analysis.

Groups often encountered are:

  • Internal ReferrerThe internal referrer is a page URL that is internal to the web site or a web-property within the web site as defined by the user. Not all tools report internalreferrers as a group.
  • External ReferrerThe external referrer is a page URL where the traffic is external or outside of the web site or a web-property defined by the user.
  • Search ReferrerThe search referrer is an internal or external referrer for which the URL has been generated by a search function. Many tools segment and report on search referrers as a group; however the exact definitions vary from tool to tool. Most will include the “big” search engines, such as Yahoo, Google, and MSN/Live. However, they vary in whether or not they exclude mail servers from these sources, or whether they use wildcards to capture any URL containing the word “search.”
  • Direct Navigation (aka No Referrer)The referrer value is empty or null. An empty referral string is often assumed to indicate that the user either directly entered the URL or selected from a list of bookmarks, but this is not always the case. Some user agents such as email clients, news readers, ad servers, and others may not set the referrervalue in the request header and thus the referrer is unknown.
Page Referrer

Describes the source of traffic to a page.

Session Referrer

The first page referrer in a visit.

Visitor Referrer

The first page referrer in a visitor’s first session.

Appending Information to URLs to Determine Source

Most web analytic solutions provide the ability to define custom variables like campaign, channel and a pre-defined source.  By appending information to URLs that drive traffic to your site (like on web pages, emails, tweets) you can more easily group data to determine campaign effectiveness.

Summary

Understanding your traffic sources is important in determining the effectiveness of your online campaigns.  Keep in mind, however, that this is just one piece of the puzzle.  Check back this week for upcoming posts to answer the remainder questions:

  • Why did they come? (motivation)
  • What did they do? (activity)
  • What did they think? (perception)

Web Analytics Solutions

I’ve listed a few web analytics solutions below.  It’s not an all-inclusive list so please feel free to comment about others.

Free or Free Trial
Popular

A Model to Improve Traffic Conversion, Internet Marketing, Software Product Management, User Experience, User Experience Jobs, Web Analytics , , , , , , , , , , , , , , , , , ,

A Model to Improve Traffic Conversion

January 8th, 2009

Tad Miller has a great post about how to combat some of the issues with advertising dollars shifting to PPC in  (Advertising Dollars are Shifting to PPC.  Now What?) One of his recommendations is to

…re-allocate the extra dollars to optimizing your website or landing pages to improve your conversion.

I couldn’t agree more.

For over a decade, I’ve struggled with gathering the right tool-set to provide me with the “complete picture” of my site’s traffic in an effort to optimize the site and increase the return on investments from my marketing campaigns.

No Complete Solutions

To my knowledge, there are no solutions that provide the 360 degree view of site visitors, but several solutions may be combined to get it.  This post isn’t about the solutions themselves, but in what I’ve modeled as the information needed to provide optimal conversion.

Note: Obzervant is building software to serve this need and more.  But in the meantime, a good review of the currently available tools  is warranted and planned for near-future posts.

What You Need to Know

To recommend and prioritize changes that improve conversion rates, 4 questions need to be answered about your traffic:

  1. Where did they come from? (source)
  2. Why did they come? (motivation)
  3. What did they do? (activity)
  4. What did they think? (perception)

360 Degree View of Your Visitors

Model Overview

The model requires both quantitative and qualitative information.  It also separates intent from result to achieve the information required to make recommendations for optimal conversion.  Keep in mind that data changes based on your visitors.  Constant analysis and monitoring of the data provides a good basis for perpetual and iterative improvements.

Source

Answers Question: Where did they come from?
Type of Data:
Quantitative
Intent or Result:
Intent

Web analytics solutions provide information about the domain and exact url that brought the visitor to your site.  You can also define and  append parameters like source and campaign (e.g. sr=linkedin, cm=banner ad) to urls to learn even more about the referring site, creative element, etc.

(Learn more about traffic sources in my follow-up post, “Analyzing Traffic Sources: Where are your visitors coming from?“)

Motivation

Answers Question: Why did they come?
Type of Data: Qualitative Data
Intent or Result:
Intent

Understanding your visitors’ reveals purpose… intent.. motivation.

Laboratory usability testing involves participants that are given scenarios and are asked to perform tasks.  And while this type of usability testing is  a very effective tool in some instances, users are not self-motivated.

Quick polls asking the user of their intention is a valid means of determining intent.  Only after establishing intent can we measure whether the user completed their intended goal.

(Learn more about motivation in my follow-up post, “Finding Motivation: Why Did They Visit?“)

Activity

Answers Question: What did they do?
Type of Data: Quantitative
Intent or Result:
Result

Again, web analytics provide information about the visitors’ journey while on your site.  Data collected may include page views, time on page/site and clicks.

If the solution provides an ability to set up goals, you can also look at the number of visitors achieving a business goal.  By establishing intent from the user, you can analyze the percentage of visitors achieving their goal as well as the effort involved (time to complete, number of pages and effort).

Perception

Answers Question: What did they think?
Type of Data: Qualitative
Intent or Result:
Result

Triggered, exit and follow-up surveys provide key information to understand visitor satisfaction.  There are methods to gathering each of these that are user-friendly.  I personally hate surveys and close them whenever I see them.  However, there are ways to gather qualitative information without the users perceiving that the effort involved in providing you with that information will be arduous.

Challenge the Model

There you have it: a quick overview on a model for gathering information needed to increase conversion rates through site usability and traffic quality recommendations.

Over the next several posts  I will explain each section of the model.  Until then, I’d really appreciate your feedback.  Help me fine-tune the model by challenging it!

A Model to Improve Traffic Conversion, Internet Marketing, Software Product Management, User Experience, Web Analytics , , , , , , , , , , , , , , , , , ,

How to recover from the worst online retail season ever

January 2nd, 2009

comScore reports online sales declined 3 percent this holiday shopping season making this the worst online retail season - ever.  With aggressive price slashing and free shipping promotions after CyberMonday (the first Monday after Thanksgiving),  one shutters to think about their profit margins.

Here’s an even more interesting tidbit  gleened from the data: although some e-tailers like Best Buy  experienced a decrease in traffic  (17%),  overall online traffic during this holiday retail season increased 5%  over last year. Here’s a summary of what we saw in online retail over the past several weeks:

  • A decrease in traffic
  • A decrease in sales
  • A increase in discounts and promotions
  • A decrease in household income
  • Virtually no change in traffic conversion rates (see fireclick index - 1 year)
Hitwise: Retail 500 - Household Income % Change 2008 vs 2007

Hitwise: Retail 500 - Household Income % Change 2008 vs 2007

The #1 way e-tailers can increase their profit margins will be to increase their conversion rates. 

How to do this:

1. Collect online metrics and make them visible

You know not what you do not know.  There are free  and paid web analytics programs out there.  Implement one.

2. Define “conversion”

What are your primary goals for the visitors you are attracting? Registration, purchase, referral?  Set up goals in your web analytics framework to define a “conversion”.   Be wary of SEMs that define a conversion as a landing page clickthrough.

3. Evaluate campaign effectiveness

Evaluate your referrers and sources (site your visitors are coming from and the campaign that drove them to your site).  How much are you spending to invite each visitor?  How many visitors converted? 

4. Shift lower performing campaigns to campaigns that are more effective

Duh.  But without visibility to metrics, defining goals and evaluating effectiveness this is kinda hard.

5. Remove barriers to conversion

Don’t get in the way of visitor that has made the decision to purchase, register or interact.  Make it easy for them to fulfill the goals you’ve set.  Improve the user experience.

Increasing conversion rates through site usability and traffic quality improves ad effectivenss and will help e-tailers recover from the worst online retail season ever.

Internet Marketing, User Experience , , , , , , , , , , , , , , , , , , ,