# Excellent Analytics Tip #8: Measure the Real Conversion Rate & "Opportunity Pie"

The topic of my speech at the E-consultancy Online Marketing Masterclasses 2006 in London is "Conversion Rate Optimization: What, Why, How".

While working on one of the slides (Tip # 9) the realization dawned that we measure conversion rate rather sub optimally and in a way that grossly overestimates the improvement possibilities.

This post will cover how you can improve your Conversion Rate in ten minutes by doing nothing more than applying simple math or by doing some really amazing investigative work you can figure out what your Real Conversion Rate (TM) is and help your company figure out what the actual size of the opportunity you have on your website to convert Visitors.

Even though we should not obsess about conversion rate we do. Mostly because short term goals drive a lot of what we do and if you are selling something on your website then it only seems to make logical sense that we measure conversion rate and get it up as high as we can as fast as we can. Another reason is that we over estimate what is possible.

Stepping back for a moment here is the definition of conversion rate that is recommended:

Conversion Rate = Outcomes / Unique Visitors

[For exhaustive details click here. And no that is not Visits or Total Visitors in the denominator, for my perspective on why that is sub-optimal click here and read the part about Why use Unique Visitors.]

So a random ecommerce website gets 1.075 million Visits from 768,000 Unique Visitors. That results in 16,500 orders giving the website a nice little conversion rate of 2.1%.

Seems really low (not really because last quarters shop.org’s study pegged the industry conversion rate at 2.2%). You show that to a Director / VP / CMO and their first thought typically is “how the heck is it possible that our website is so bad that we can’t get more of 751,500 (768,000 – 16,500) people to convert on our website”.

• Unique Visitors to Website: 768,000
• # of Outcomes (Orders/Leads etc): 16,500
• Conversion Rate: 2.1 %
• Opportunity Pie: 768,000 minus 16,500 equals 751,500

From there it is just a nanosecond computation that will be given to the person responsible for the website: “If you can just get another One percent of that 751,500 converted, just a measly One percent, then it would increase our orders by a humongous 46%!!!” [(751,500 * 0.01) / 16,500]

It seems very logical (very reminiscent of many entrepreneurs who head off to China dreaming of massive success by converting just one percent of the Chinese population). The problem with the logic is that is presumes that the size of the left over pie is that big (751,500). The reality is very different.

The fastest way for you to improve your conversion rate is to figure out what is the number of people who are in play for even remotely being converted. Here are three suggestions on how to do that (and figure out what the opportunity pie looks like):

# 1: Use Bounce Rate.

Bounce rate helps identifies the % of traffic to your website that “leave instantly”. It happens for any number of reasons: wrong clicks in search results or reaction to the website or missing promotion on the page or any other reason.

Bounce can be defined as anyone who was on the website for less than five seconds or ten seconds or anyone who has viewed only one page. After analysis of different websites I have recommended using ten seconds as the criteria. That’s the minimum time that someone has to commit to your website, just ten seconds, for you to even have a chance of convincing that visitor of anything.

So measure Bounce Rate of your website. A “normal” bounce rate is around 30% (YMMV). Here is the impact on Conversion Rate:

• Unique Visitors to Website: 768,000
• Bounce Rate: 20 %
• Unique Visitors “in the play”: 614,400
• # of Outcomes (Orders/Leads etc): 16,500
• Real conversion Rate: 2.7 %
• Opportunity Pie: 614,000 minus 16,500 equals 597,900

Using traditional computations you would overestimate the size of pie (folks you could possibly convert) by 153,600!

# 2 (If you use Web Logs) Filter out search bots, image requests, 404 errors, website monitoring software "visits" etc.

Some analytics professionals are still using weblogs as the source of data for doing Web Analytics. This might be sub optimal for many reasons (more on this one of these days) but one of the primary reasons is that web logs will natively incorporate the visits by search robots (and even if we try to filter these out it is hard because new ones pop up every other day). This inflates visitor counts, if not filtered.

Web logs can also contain “visits” by various site monitoring software and inflated number of page views (404’s and spurious requests you might have on your website like dll’s and css and on and on) which will not allow you to compute bounce rate accurately.

So do your best to filter all the above stuff out. Normally this can take out between 10% to 30% of your visitor data (depends on many factors so YMMV). Here is the impact on Conversion Rate:

• Unique Visitors to Website: 768,000
• Crud Filtered Out: 25 %
• Unique Visitors “in the play”: 576,000
• # of Outcomes (Orders/Leads etc): 16,500
• Real conversion Rate: 2.9 %
• Opportunity Pie: 576,000 minus 16,500 equals 559,500

Using traditional computations you would overestimate the size of pie (folks you could possibly convert) by 192,000!

# 3 Use Customer Intent

One of the biggest mistakes business make is thinking that every visitor to the website is fair game, conversion fodder.

Close your eyes and imagine walking into a car dealership. You are greeted by a car sales man whose only objective is to do whatever he/she can to sell you a car today (not even tomorrow, today), mostly because they are paid on commission. The problem is that you are there just to look at the car, maybe take it for a test drive. You have not yet saved up enough to buy a new car. You really don’t want to be sold.

To the guy in a suit that does not matter, he is going to bring it on rather than focusing on what you want (and it is not his fault, incentives drive weird behavior).

Similarly not every Visitor to your website is there to buy and not very visit by a visitor is a opportunity to convert. Yet we do Path Analysis and measure conversion rate they way we do because we behave like that car salesman.

Using Market Research or Website Surveys or other methods attempt to compute why Visitors come to your website (I call this Visitor Primary Purpose). Then segment out Visitors who say they are there to 1) Buy and 2) Research (/learn about your products and services).  You’ll find other segments of people who come to your site looking for support or company information or jobs or register their products or update their contract or check status of their orders etc etc.

You should be converting 100% of #1 (Purchasers). You’ll never hit 100% but work hard to create a frictionless process for them. You should convert a good amount of #2’s (Researchers / Shoppers), not all want to buy but they are fair game.

Normally you’ll find that around 15% of your site traffic is there to buy (Purchasers) and around 20% is there to Research / Shop. Giving you a total of 35% (again YMMV, but I promise you this number is half of what you think it is for your site). Here is the impact on Conversion Rate:

• Unique Visitors to Website: 768,000
• Potential Visitors who can be Converted: 35 %
• Unique Visitors “in the play”: 268,800
• # of Outcomes (Orders/Leads etc): 16,500
• Real conversion Rate: 6.1 %
• Opportunity Pie: 268,800 minus 16,500 equals 252,300

Using traditional computations you would overestimate the size of pie (folks you could possibly convert) by 499,200!

Let me express that another way: When your Director / VP / CMO asked you to improve conversion rate you were overestimating the amount of Visitors you could possibly convert by half a million!

Something that to the CMO looked “so easy” for you to accomplish is a nothing short of walking on water for you. I am exaggerating a bit of course, but not by that much.

You can now imagine that reality of the world is a little bit worse. # 1, # 2, # 3 above are not silos. So some Purchasers and Researchers will Bounce off you site because they landed deep into your site and on the wrong page. You can imagine more scenarios like this. Which means the real number of visitors who had the right intent and who stayed long enough to give you a chance to convert them is small.

Now you can easily see why we all work hard on analytics and marketers work so hard on content and copy and offers but we can’t seem to move the conversion rate by all that much. The reason is that our denominator is incorrect (in our standard formula conversion rate equals outcomes divided by unique visitors).

Recommended Actions:

1. Measure conversion rate as everyone else does, just so you have it and then ignore that number because it is deeply misleading.
2. Measure your Real Conversion Rate (TM)  by applying the above recommendations (or use your own because you'll have unique things that apply to your business).
3. Undertake a repetitive education program in your company to educate your decision makers the size of the real opportunity on your company’s website.
4. Segment the Visitors in the Opportunity Pie to identify what their true levers are (in getting them to buy). Focus on the Why (use Surveys or Lab Usability or Experimentation & Testing for example).
5. Sit back, relax and enjoy the ride because you have achieved the pinnacle of Web Analysis! : ) [Oh ask for a bonus, Jim this one's for you!]

What do you think? Is Real Conversion Rate metric a good one? Do you already use it and this is old news? Do you have suggestions on other ways in which to compute the Real Conversion Rate? Any flaws in the above analysis / recommendations? Please share your feedback via comments.

1. 1

Hi Avinash,

2 hours ago I had the exact same experience you have given as an example, with my Acquisition Director. Very actionable post for me, I will certainly use your suggestions.

However, I do believe we should also divide our CONVERSION RATE into sub-conversions. I don't know if I read it somewhere else, but I like the approach of webpage conversions, or persuasion like the Eisenbergs would say. Well, you still have the distortions you discussed above, but much smaller ones. For example, if I am measuring the conversion of one of my internal pages, it is less probable that the visitor got there by mistake.

As for the log files issues, I agree 100%. I am writing my M.Sc. on Web Usage Mining, and I am just astonished with what I see. ALL the research on the subject is based on mining Log Files, and there are some researchers that use data mining techniques using ComScore data to analyze a specific website behavior. Amazing, isn't it?

The customer intent is more difficult to measure. I think the way people treat you is highly influential in your decision to buy, so I feel there should not be a big difference on the way you treat research/purchase visitors. I think.

Anyway, very good insights, thank you.

Daniel Waisberg

2. 2
Jacques Warren says

Hi Avinash,

I would calculate the CR on total trafic, so that I have an idea of the "General Output" of the site, and on the process (transaction, subcription, request, etc.) which I analyze to get a sense of the crucial drops (I mean, these are people who DID start the process). If the client is willing to spend the money (which I try as hard as possible to convince them to do), we conduct an attitudinal analysis in order to evaluate true intent, which gives us a much better sense of the real opportunities (both in CR and missed).

The General CR is still what's around when people talk about it, and, in a sense, is not such a bad metrics, if everyone knows it is a 10,000-foot view of one's site output. However, your RCR (tm?) is definitely closer to reality, and gives a better view of what lays there in terms of opportunities. I also suggest that the process CR is really the most important one, since understanding where and why people drop from the process will have the most dramatic impacts on the output.

3. 3

Hi Avinash!

Really enjoyed reading this post..which I viewed on my handheld…found it easier to aborb what you have to say on a small screen.

It's really interesting how you calculated the real conversion rate of a site….it turns out to be higher because the real number of unique visitors that can be converted is lower than you think.

Did you trademark that formula? I see a "TM" next to "conversion rate". If that's so..are we paying you royalties everytime we figure out the real conversion rate? Just joking.

Thanks for the great post!

4. 4

I agree with much of this and I applaud you for driving examination of the CR metric forward in the thought process.

So much depends on the purpose of the landing page and how many other factors add noise to the funnel. For this reason I have begun to analyze page performance (and challenge my clients to as well) based on how many users the page can drive closer to their goal. I call that metric engagement and it is based on clicks on the call to action desired by the stakeholder. Then we take that number and look at optimizing it for conversion. What I think this provides is a truer sense or filter for the "customer intent" you describe, and that I think is the most important part of this post.

So maybe, in a multi-page funnel, conversion from external referral traffic to the page isn't a very good metric at all?

5. 5

Daniel: Dividing the metric into "sub conversions" is a great idea, of course the crux of the matter is in what "sub" actually means. Most "subbing" is good. I am not a huge fan of measuring conversion rate of a page.

In a complex unstructured multi-page experiences how do you give "credit" to one page? Just because someone saw it? Having done so much usability (lab, site visits and remote) I have lost all my faith that a Page View means anything except the fact that the page was viewed. No implication of good or bad (except for the "thank you" page after Submit Order which is a sure indicator of success).

There are always exceptions, one such exception is in Jonathan's comment above. In a structured experience (Landing Page -> More Info -> Add to Cart -> Checkout) we can measure conversion rate of one Landing Page compared to another.

Food for thought.

Marshall: The "TM" (trademark) is part ironic, part funny, part branding, part "let me see what happens". All inspired by this post from the ever wonderful Seth Godin:

http://tinyurl.com/yfhdx2

So I have "TM'ed" Real Conversion Rate!! No royalties will ever be demanded! :)

Jonathan: I think it depends.

In experiences where the "noise" can be controlled (say PPC/SEM campaigns for specific keywords landing on custom created pages) I think it would make sense to measure conversion from external traffic because it tells you something about the choice you paid in spending money on that acquisition.

In other experiences we can make a case that is might not be a good metric.

Thanks to the three of you for some sparkling conversation as a result of your thoughtful comments.

6. 6

Hi Avinash,

In a complex unstructured multi-page experiences how do you give “credit” to one page? Just because someone saw it? Having done so much usability (lab, site visits and remote) I have lost all my faith that a Page View means anything except the fact that the page was viewed. No implication of good or bad (except for the “thank you” page after Submit Order which is a sure indicator of success).

In fact, what I meant was not to count page views as single page conversions. Rather, I believe that every page must have a purpose to exist (like ourselves ;-) so if you have an objective you can measure it.

For example, a product page wants to convince you to buy, a purely informative page wants you to just stay on the site and not leave, About_us page wants you to know more about the website and continue the visit (or go to the our_store_address page) and so on. Every one of these objectives can be measured somehow, IMHO.

Does it sound better?

7. 7
Mayra Harley says

Learned a new way of hashing data. Thanks for the sharing your view!

8. 8

Hello everyone:

Sorry to crash the party – I take a different perspective on the whole problem: I don't think that a conversion rate of 2.1% translated into a real conversion of 6.1% should make the CMO happier. I believe CMOs should be concerned about their company's conversion rates compared to meaningful benchmarks.

This is similar to a CFO who can slice and dice his numbers in various ways but at the end of the day, the company will be judged based on metrics (e.g. ROE, profit margins) compared to other meaningful benchmarks.
I would appreciate your thoughts – particularly Avinash's ;)

Antony

9. 9

Antony: You are not crashing the party! :) We have shared vision on having comparable and meaningful benchmarks. The core thrust of the post is on two things…

1) Figure out what the real conversion rate is so that we/CMO have a good idea of what the Real performance. This is the spirit of gaining a understanding to the real micro visitor trends on the website.

2) To educate ourselves, and more importantly, and the CMO of what the size of the opprotunity is so She/He can make good decisions. Today that simply does not occur becuase it seems easy to convert another 10 out of 98 people, it is stunningly hard to convert 10 out 30.

Hope this makes sense. Thanks so much for the comment and thought.

-Avinash.

10. 10

See the official Future Now, Inc. response at http://persuasion.typepad.com/architect/2006/11/your_unreal_con.html

11. 11
Daniel says

Very usefil bit of information you provide. Slightly off topic, what would you consider today to be the minimum unique visitors number to be attractive for advertisers outside friends and family circles. Are there any resources giving some indications about what traffic levels on average generate in real or potential revenues? Tx. D.

12. 12

Hi Avinash,

Agree with your filtering advices to get a more insightful conversion rate. I just published a post in our blog regarding this and Future Now's 'offical response'.

Don't give up, you're helping lots of website owners with your Excellent tips ;-)

I won't be able to make it to London in a couple of weeks but I'm looking forward our next rendez-vous ;-)

René

13. 13
Steve says

FYI: Running the numbers regarding the "Crud".

Difference of ~ 27%, for us, by Visits & Pages.
~ 2% by Visitors (Unique).

For busier sites, I find that the Crud doesn't seriously impact the more "at a glance" useful metrics. Most bots et al, come from the same IP addresses so this does make sense. :-)

For detailed analysis, the Crud Must Go(tm).

– Steve

14. 14

I think the last aspect of your excellent tipp is the biggest thing. It is again all about segmenting. Segment your conversion rates into users who want to buy and and set up a conversion event for buying (easy) and users who just want to gather information and setup conversion events for succesfully gathering informations (harder). The story continues of course. And you could always watch users moving from one segment (user lifecycle) to another one…

15. 15
venkat says

Hi Avinash,

The article does give some idea about calculating it right. But how does that really help in the long run? For short term to show to my superiors, it looks good. But we work on 'improving' things.

As long as i use a consistent denominator (regardless of real denominator or unreal denominator in your words), the increment/decrement in the conversion rates would indicate the happenings the same manner. An example (no html) is the sales increased, the visitors increased. There is no change improvement in the conversion rates calculated in real or unreal way.

Quarter 1 Quarter 2
Unreal Real Unreal Real
Sales 2 2 3 3
Visitors 100 75 150 112.5
% conv rate 2.00% 2.67% 2.00% 2.67%

I think, the recommended action item no 4 is taken up generally anways.

Thanks,
Venkat.

16. 16
Anil Batra says

I like the apporach in general but have differing view on point #1 and point #3. Since it is too big to fit here, I have blogged it on my blog, you can read it at http://webanalysis.blogspot.com

17. 17

It is good Article for business man and for SEO to learn about Conversion rate. There are many few resources who spread this knowledge. After reading this articles and using google.com/analytics toot, SEO may convert traffic to conversion rate.

18. 18

Hi Avinash,

Thanks for the note above on tracking real conversion rate. It really provides deep insight into the conversion rate metrics for any website.

19. 19
Jae Jans says

What can I say?

While searching for some info on conversion rates I stumbled across this article.

It rocks and it's an idea I never really entertained before. It makes sense. But what percent of that "bounce" as you call do you think is possible to capture if you added the right element to your page?

I'll be following your work and hope to check out your book soon!

Jae Jans

20. 20

It's certainly useful to know how much traffic is essentially "noise" that can't be converted.

I've personally found that the most effective way of increasing my conversion rates, apart from testing, is to use a "mind reading" technique which gathers the thoughts of a visitor at particular points on a site.

In other words, at the end of a major section of your site (such as after explaining a major benefit), you can ask for feedback from the visitor on whether they understand – and if not, you can elaborate.

This kind of interactivity gets people involved, and provides me with valuable feedback as to what is going on in a visitor's mind at the time. I use my own software to do this.

21. 21
Glenn says

Very interesting post. I do wonder though if bounce rate should be treated entirely as something you can't improve. They say first impressions last, and I know if I'm looking to buy form a site how professional or "polished" it looks goes a long way. If it looks like something an 8 year old could have constructed, I'll take my eyeballs and wallet away immediately.

22. 22
Rohit says

Great post, elaborated nicely. Besides your advice, I would like to add: Targeting appropriate audience plays important role in increasing conversion rate. Some keywords convert like 80% (yes, thats true). Also the bounce rate consideration is not applicable for a site selling product through a pitch/sales page which has all information on one page with a proper action to call which takes buyer directly to payment gateway page.

23. 23
Alex B says

I have to admit Avinash, this post seems to fly in the face of many things you have advocated in the past, and also runs afoul the whole "Unique Visitor" debate that seems to have consumed a fair portion of the community.

I'll cut to the chase– what good is this doing? Sure the conversion rate is higher, but that doesn't tell you anything because the entire calculation has changed. How does this fit with measuring trends? What's wrong with having a broader pool? Sure, the "real" number might be higher than we give it credit, but since when did that matter when we're looking for progress, not absolutes?

24. 24

Alex: Let me try to clarify…

One of the most insidious problems for companies is that they over estimate their "conversion opportunity". Traffic went up from one million visitors to two million visitors so we can now make twice the amount of money. The reality could very well be that you got a additional 100% irrelevant traffic (all of whom who wanted to buy underwear and you sell ipods, or all who wanted to read your blog, or all who only wanted the one job you have listed on your site etc etc etc).

By presenting this framework I was hoping that the Analyst could give a reality check to the CXO as to what is actually possible in terms of bottom line impact.

Few Analysts sit down and think, what's the actual size of the opportunity in front of is. We all thing its all Visitors to the site. False.

If that primary goal is accomplished then there are two secondary impacts (in this order):

1) We realize we don't "suck" as much as the 1.72% conversion rate seems to indicate. So let's make sure we internalize that, get credit for it, and segment the data like heck to find growth opportunities in terms of conversion sources (sources that might otherwise be "hidden" in the big pool).

2) We realize that we do "suck" that our opportunity pie is so small (if indeed that is the case). That should force the Marketers / Directors to realize we are getting a lot of sub optimal traffic (call it "unqualified", note the quotes), then ask the question what do we do? A] We can figure out what to do with this "unqualified" traffic (that is bouncing or there for the wrong reasons etc), create content for them, engage them, etc etc. B] Start targeting our campaigns better so we can increase the opportunity pie (qualified traffic).

Net net, I am not encouraging a numbers game. I am encouraging a different way of thinking of the numbers so the above core Organization Behavior and the Organization Campaign Spend problems are seen in a more stark light and hopefully solved.

Looking at the data in aggregate I think hinders that.

-Avinash.

25. 25
e c says

The Conversion Rate is a indication to how success is your website sales, every one try to increase it, I think having a good landing page can increase this rate, also using the above info we can measure it correctly and boost the rate higher

26. 26

Hi Avinash,
Interesting post. I wanted to know your thoughts about removing the bounces from the unique visitors in denominator.

For the sake of example, let's consider that our site is an online mall. By the nature of the website, the primary purpose would be to get customers to buy.

If we subtract all the bounces from the visitors, we are assuming that these customers got to the site due a incorrect search result, not interested at all etc…However, (IMHO) we also factor the phenomenon that online buyers will most probably compare prices across websites (or even showroom). It might very well happen that a site visitor lands on a product page, sees the prices and closes it (adding to the bounce figures). I would want to include such visitors in my unique visitors (denominator) as whether I like it or not, they did abandon on seeing a product.

My question is 2 fold: What's your thought on this and if yes, how do you think the bounce figures can be better segmented to include such visitors?

Thanks.

27. 27
Steve Goldberg says

Thank you for some new ways of thinking about what people are actually doing on a commerce site, and developing a formula-based approach.

I'm a new webmaster, in the adult products field, and I've been studying the analytics, trying to see how we're doing, in a very crowded marketplace. A little better than I thought, it seems, given that we have predominantly first-visit buyers; so CR/visitors will be more accurate that CR/visits. Getting real is real good.

Thanks again!
Steve

28. 28

Hi,

This maybe a bit off topic, but I was wondering if anyone knew what denominator GA is using for Goal Conversion for apps? I know it's unique visitors for websites, so I am wondering if I can assume that it is the unique user for apps.

Thanks much,

• 29

Vladimir: In Google Analytics for websites, the normal usage, the definition of conversion rate uses Visits and not Visitors. This is not correctly stated in your comment.

In Google Analytics for mobile applications, the definition is the same and conversion rate uses Sessions and not Users.

So consistent in both cases.

Avinash.
PS: A bit more on conversions in mobile apps in GA is here: http://goo.gl/cEHfBc

• 30

Hi Avinash,

Thanks a great deal for clarifying this, for some reason I was under the impression that it was unique visitors.

It still feels surreal to have someone whose book I've read and keep on reading answer direct questions :).

Thanks for staying humble and as always, helpful.

Kind regards,

29. 31
Dom Linder says

Another action which could be suggested is to investigate the quality of your traffic sources, and to do A/B testing on your landing pages, in order to reduce the amount of bounced traffic and increase the size of the 'opportunity pie'.

1. […]  But as a fan and follower of his work, I was surprised by many of the statements in his recent post, "Measure the Real(tm) Conversion Rate & Opportunity Pie." It’s almost as if Occam cut himself shaving. […]

I'm an avid reader of Avinash Kaushik's blog, Occam's Razor, and I quietly anticipate each new post. In general, Avinash is incredibly insightful, thought-provoking, and just fun to read. But as a fan and follower of his work, I was…

3. […] Avinash has posted a week ago a new Web Analytics tip on his blog (Excellent Analytics Tip #8: Measure the Real Conversion Rate & “Opportunity Pie") and John Quarto-vonTivadar from Future Now Inc. disagreed on his blog (Your Unreal Conversion Rate). […]

4. Which Conversion Rate?…

What should your conversion rate measure? Is the typical measure of how many of your visitors buy too broad? Aren’t some of those folks hopelessly improbable prospects? Aren’t there other successful outcomes besides a purchase?

These are the question being discussed in a recent blog post from our friend Avinash and many other respected analysts who have left thoughts in his comments……..

5. […] The Conversion Rate is the percentage of conversions that occur in relation to overall site visits – or at least that is how most people define it. But not Avinash Kaushik.

Avinash is an obvious thought-leader when it comes to web analytics. Recently, he had a couple of really great points about Conversion Rate and how to properly assess the real conversion opportunity pie (i.e., how not to overestimate the number of 'convertable' visitors). […]

6. visualising a customer funnel…

Increasingly, our work at Red Ant involves understanding how customers are using and responding to something online. By tracking and measuring how people interact with a particular site / game / online form, we're able to improve and adjust…….

7. […] There is an interesting discussion on working out just how leaky your funnel is and setting realistic targets for the top of your funnel in Measure the Real Conversion Rate & "Opportunity Pie", and then debunked in this post. […]

8. […] … Even though we should not obsess about conversion rate we do. … Stepping back for a moment here is the definition of conversion rate that is recommended: … Read more: here […]

9. […] But as a fan and follower of his work, I was surprised by many of the statements in his recent post, "Measure the Real(tm) Conversion Rate & Opportunity Pie." It’s almost as if Occam cut himself shaving. […]

10. […]

In einem exzellenten Artikel berichtet Web Analyst Avinash Kaushik über Konversion und Zahlen. Eines der Hauptursachen für eine Fehleinschätzung des Potentials ist die Annahme, dass alle Besucher auch potentielle Käufer sind. Das sind sie nämlich nicht.

In aller Kürze hier die Hauptaussagen von Avinash Kaushik:

1. Rund 30% aller Besucher gehören normalerweise in die Gruppe derjenigen, die nicht einmal 10 Sekunden auf einer Webseite verbleiben und gleich wieder gehen. Das hat verschiedene Gründe, meist ein Fehlklick.

2. Weitere 5% können für Besuche von Bots, Screening Programmen und anderen gesteuerten “Besuchern” hinzugerechnet werden.

[…]

11. […] Excellent Analytics Tip #8: Measure the Real Conversion Rate & “Opportunity Pie”? […]

12. […] The marketing funnel above shows the several online response behaviors that culminate in an online purchase transaction, starting from the impressions for the Ad (100K) shown on Facebook with 4 visitors completing the purchase transaction (this goes through a 3rd party shopping cart service). For this particular campaign above, we measured the goal conversion rate to be 10% overall. We found that by carefully qualifying the text on an Ad creative, we had an effective way of preventing clicks for users who have no intent to buy (upon click-through). This effectively reduces CTR, but if targeting is right on, and improves over time, this should increase conversion rate, and this conclusion was born out by the data. Such creatives and Facebook's provision of targeting specific user profiles was employed to direct some of the campaigns. You can find an extensive discussion on measuring conversion rates across funnel levels here […]

13. […]
Case in point, if you have a large number of visitors that come back to your site to make a purchase the second time around, maybe its even from another computer or mobile browser (remember, analytics considers each of them a unique visitor), you really have one conversion per two visitor sessions instead of one customer and one conversion. While I’m not here to point out the problems with how we measure conversion rates, it is worth noting how visits to purchase is correlated to conversion rates – typically speaking sites with a heavier weighting of a single visit to purchase have higher reported conversion rates. However, in reality, they may not fare as well as another site with a lot of customer engagement but might convert more on the second or third visit.
[…]

14. […]
Before continuing, let me explain the conversion opportunity concept as it relates to your website. The conversion is the same as in the brick and mortar world: you want to make a non-client into a client. In this situation, you have winnowed down the people who will encounter your conversion opportunity to people who are interested enough to be at your website – i.e. either your clients or your prospects. Now, give the prospects an actionable opportunity to “do something.” Offer them a white paper about somethign related to your field in exchange for an email address, for example. Then, with that email address you can maintain contact and offer them more expert information and more opportunities to become clients.
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15. […]
El porcentaje de conversiones indica la relación que existe entre los accesos al site, y las veces que esos accesos acaban en venta. Un 100% indicaría que todas las visitas acaban en compra (o que todos los usuarios acaban comprando). Eso, evidentemente, es imposible. No todos los usuarios que acceden a una web, aunque sea exclusivamente de venta online, tienen intención de comprar. Pueden necesitar la dirección de las tiendas físicas, o atención post venta, o quizá desean cancelar un perdido. Tal vez sólo estén buscando información (en este sentido, conviene tener claro el concepto de Opportunity Pie).
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2) Learn which mission critical pages have a high bounce rate
A common bounce rate is 30 – 60% according to Avinash Kushik. Check your mission critical pages to know which ones have a bounce rate above your site’s average. Use Google Analytics to pull a report of top visited pages and their bounce rate.
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A common bounce rate is 30 – 60% according to Avinash Kushik. Check your mission critical pages to know which ones have a bounce rate above your site’s average. Use Google Analytics to pull a report of top visited pages and their bounce rate.
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Nella famosa “opportunity pie” di Avinash Kaushik viene spiegato che, fatto 100 il numero degli utenti sul tuo sito, esiste:
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Excellent Analytics Tip #8: Measure the Real Conversion Rate … https://www.kaushik.net/avinash/The topic of my speech at the E-consultancy Online Marketing Masterclasses 2006 in London (sign up here) is "Conversion Rate Optimization: What, Why, How". While working on one of the slides (Tip # 9) the realization …
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Bounce rate helps identifies the % of traffic to your website that “leave instantly”. It happens for any number of reasons: wrong clicks in search results or reaction to the website or missing promotion on the page or any other reason. More info here.
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Back in 2006, Avinash Kaushik published this post about measuring the real conversion rate and opportunity pie. The way a standard conversion rate is calculated in GA (number of conversion completions divided by number of sessions) is actually overestimating the possibilities for improvement.
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Context, in reporting, increases accuracy. Not to mention, credibility. That’s why Google Analytics is so underrated. It packs serious data, but most often, you need to customize the data to see valuable insights beyond impressions or clicks. Another amazing report is the conversion opportunity pie, courtesy of the magnificent Avinash Kaushik.
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Rather, blogging drives traffic that requires a constant back-and-forth to move through your funnel. With blogging, you’re also going to get a lot of junk. The vast majority of traffic will never buy anything (see: opportunity pie).
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Typical website conversion rates suck. Why? The majority of traffic doesn’t care about your product or service and won’t convert. The Opportunity Pie theory by Avinash Kaushik proves this.
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Typical website conversion rates suck. Why? The majority of traffic doesn’t care about your product or service and won’t convert. The Opportunity Pie theory by Avinash Kaushik proves this.
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