Pear Analytics

Keyword research is one of the most important steps for good SEO of your site.  First let’s start with understanding what keyword research is. Essentially keyword research is understanding which keywords you want to target (for each page in your site) and which search terms you want to be found for on search engines.For example if you are a php consultant in California you probably want to be found for the terms ‘php consultant’ and ‘php consultant California’.

So why use a keyword research tool in the first place? A keyword research tool will give you more information about the words you want to target and also ideas of which words you could target. So assuming you are a php consultant then the keyword tool will tell you how many times people search for the keyword you want to be found for. For example the term ‘php consultant’ gets 590 searches a month approximately. This way you don’t target terms which have very low search volumes.

Typically comparing numbers between keyword research tools is similar to comparing numbers between different analytics tools. There will always be a frustrating difference. When comparing different keyword tools, there is usually a minimum difference between numbers in the range of 10-30%.

For example, lets compare numbers for the keyword ‘buy domain‘ in three of the most popular keyword tools:

1. Google Search Based Keyword Tool shows monthly volume as 8200

2. Google Adwords External Keyword Tool shows a 6600 monthly volume for the same keyword.

3. Keyword Spy shows a monthly search volume of 135,000! This huge difference is probably because they are showing ‘broad search’ numbers as opposed to the exact search numbers.

So what should you do? Here are my recommendations:

1. Use one tool and stick to it’s numbers:  There will always be a difference in numbers between tools because of the way they collect data, whether it’s a broad search or exact search. I wouldn’t recommend using two different tools and reconciling data between tools. The three tools metnioned above are pretty good and I personally mostly use the Google Search Based keyword tool  because it gives me valuable information about how competitive  a keyword is. Keyword Spy is useful to understand what keywords your competitors are bidding for in Adwords . Google Adwords tool is useful when you are out of ideas for keywords because of the number of suggestions it generates. The important thing is to never mix data from two tools and make inferences.
2. Use keyword research data as data points relative to each other :For instance if the keyword ‘buy domain’  gets 8200 searches per month and another keyword ‘buy web domain’ gets 440, instead of focusing purely on the absolute numbers the takeaway should be that ‘buy domain’ gets approximately 20 times the search volume as  ‘buy web domain’
3. Never make assumptions: Always tie in SEO with the numbers on your Analytics tool. You may rank for a competitive term on the first page of Google and assume (falsely) that it may be driving in lots of traffic. Check your analytics reports to see how much traffic it drives. More importantly create custom reports to find how many ‘Goal conversions’ resulted from that keyword search on your site. That is the metric you want to ultimately track to measure the true success of a keyword.

Lastly,  never be bogged down by the difference in numbers.Good luck with your keyword research!

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The Pear Analytics Website Analyzer tool has analyzed nearly 5,000 unique websites since we launched it in March this year.  We’ve helped many website owners make changes themselves with our “Fisher-Price” instructions to get their site more search engine friendly.

Now we’ve kicked it up a notch.  Now we’re offering to fix parts of the site for you – and for cheap.  A good portion of your searchability issues are going to be related to the technical side of your website – a place where many avoid due to the complexity and fear of breaking something.

There are 2 options for you too – we will fix the problem and you install the changes, or for a bit more, we will fix and install the changes for you.  If you want us to install it, we will simply send you an invitation to allow us to briefly access your computer while we work our magic.

Give it a shot and start the process by analyzing your website.

I’d love to know what you think.

1 Comment »Tags: SEO, seo tools, website analyzer

While doing research on page load times, I came across a lot of articles regurgitating the same study. Getting deeper into it, there were many more discussion forums where people did not agree with the studies. The most recent study on page load times and customer retention was done by a company who sells a service optimizing load times. So of course, they made a simple questionnaire asking people how long they would wait for a page to load and found most people would wait less than 4 seconds. Many people pointed out that it would depend on the kind of page they were trying to load, whether they had broadband or not, the age of the visitor as well as many other factors.
So the question is, is a study done by a company who’s selling a service really impartial? Can it be trusted, or will they skew the results in their favour?
How long will you wait for a website to load? Is 4 seconds too long? Does it depend on the website? Will you wait longer for a specific site or go search for something else?

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That’s right – you can’t measure everything online that you might think.  Analyzing click traffic on websites has become much more difficult to get anything close to accurate.

One of the most difficult problems to solve is the issue with giving proper credit to the “original source” of the lead or sale.  Some of the PPC systems refer to this as the “assist” and they pass special tracking cookies to the user that will help indicate in the click stream data future visits from this user.  This typically helps credit PPC campaigns and reduces the cost per acquisition (CPA) for that channel.

This is great, but it is flawed.  This generally assumes that the visitor used one computer, and few of us use one computer.  We usually have an office computer, a home computer (we have 2), plus mobile devices.

Consider this situation (which is probably quite typical):

1.  Husband is searching for vacation spots for his family during his lunch at work.  He does several searches, including hitting a few paid ads.
2.  He runs out of time and has to get back to work, so he emails himself the links to the pages of the sites he liked to his home email account so he can show his wife later that evening.
3.  He gets on email at home and pulls up the pages on his home computer to show his wife and kids what he found.
4.  They continue to do more research and even bookmark a few sites/pages and will revisit in a couple of weeks so they can think about it.
5.  They revisit the site a few weeks later by hitting the saved bookmark and from there, decide to purchase.

Now in this case, it’s going to be virtually impossible for the marketer to track this sale all the way back to the paid search ad because he lost him as soon as he switched computers (if he is even using cookie and campaign tracking in the analytics software).  And if this happens often enough, he will think his paid search campaign is ineffective because it is not driving any sales.

Newsflash: most people don’t buy anything on the first visit!

There is likely going to be multiple interactions, extensive research, bookmarking, etc. before any purchase is made over a several-week (depending on the product) sales cycle.

Secondly, consumers are not going to be as compulsive in a down economy and are going to be looking around for deals, so we can’t possibly expect them to purchase on the first visit from a Google ad.

So what can we do about this?

Well, not too much, unfortunately.  However, if you have an e-commerce site selling any sort of products, you can reduce this phnomenon by simply having a “Favorites” or “Wish List” area of the site where a user can quickly and easily open a free account and save what they like straight on your site. This would eliminate the need to bookmark and email and cookie track everything.  You would have all of the data on your site, and now you could even do session tracking by username and get other interesting information (beware that session tracking has additional privacy issues that you will want to look at closely).

Many of the large sites like Amazon, eBay and others have this feature, but even for small or medium sized business, most of the 3rd party off-the-shelf e-commerce applications (like X-Cart, Magento) have Wish List capabilities.

Happy tracking!

No Comments »Tags: cost per acquisition, Google AdWords, PPC, Web Analytics

I’ve been paying attention to television advertising spots lately to see what the tracking mechanisms are.  Surprisingly, I would venture to guess that only about 30% of the spots (local and national) have clear tracking mechanisms.  The underlying goal is the necessity to know the impact of each media channel on sales.

The ones that are easy to identify are the ads that display a URL at the end of the spot that says something like “www.domain.com/tv32″, where the “tv32″ identifies the geographic location for a multi-location buy.  Now, it is likely that this page is not accessible through the main navigation, and may even have a “no follow” rule for search engines so they won’t index it and muddy the data.  You would simply go to your favorite analytics program and look at the pageviews for that special URL, and possibly even segment the group and track their activity beyond this page.  My question is do people really type in the “tv32″, or simply go to the main site?

Other methods use a promo code, where they send you to the main website (no special page) and will have a clearly labeled area on the home page to enter the promo code.  Each code varies based on the media, and possibly even run dates so you can identify very specifically where the traffic came from.  I like this method better because a) the ad becomes offer-based, rather than just awareness; b) it removes the likelihood of a visitor bypassing the special “/tv32″ page that was set up.

Now, you might say that the latter example mixes existing inbound traffic with new traffic created by the TV spots.  You are correct; however, we can do a couple of things to separate this out:

1.  Create a segment of visitors from the cities that the ads were run.  If you ran the TV spot over 10 different cities, then create a segment for those cities.

2.  Look at your aggregate traffic before the spots ran, during the flight when the spots were running, and again after the flight ended.  Now, if you are running TV, print and radio all at the same time, it will be very difficult to segment traffic out by media unless you use the promo code option above, but then again, those are really only the folks who would “convert”, which will be a percentage of the total visitors.

3.  Calculate the effect of increased traffic to the website by taking the gross traffic during the time the spots were running, and subtract out your baseline, or average traffic before the media blitz.

You can get more finite information if you know exactly when your TV, radio or print ads ran and comparing visitor traffic down to the hour if you wanted to.

So, given the complexity of monitoring traffic on a national media campaign based on the potential issues mentioned above, and the fact that no method will be perfect, there is third idea:

What if you were to purchase a promo URL for each medium, such as television, radio and print?  (I neglect to mention Internet here since those visitor types are much easier to track). This way your traffic would be easily segmented and not all together in the same “bucket”.  I am not seeing this being widely used, and while some may argue that it detracts from the brand itself, I still prefer to pick a method that is more “trackable” than another.

Of course, you could always do a media “hiatus” and measure the effect on sales by comparing POS data.  You could even run one media channel at a time to see its relative effect as well.

What do you think?  What have you seen?

5 Comments »Tags: marketing performance tracking, measuring broadcast, tracking conversions, tv spots

Below is a video tutorial of an example of how you can correlate offline media efforts to web traffic, and essentially understand the effectiveness of your offline media.

I use Clicky Web Analytics to help measure the the effectiveness of offline media because it can track visitors down to the street level. All of the other analytics tools I have used only go to the city level. (caveat: this isn’t exact, so don’t knocking on people’s doors or anything! Use this for relative measure of density in areas of a city).

How can marketers use this data? Well, I can drop a direct mail piece and a few days later see if I have a concentration of visitors in the neighborhoods the piece was dropped. You can do the same thing with billboards as well, although it may be more beneficial to place the boards in the areas with the most concentration (or least if you are after brand awareness). This could even work great for a nation-wide television campaign, to where you could follow-up with direct response marketing to the areas with the highest concentration of visitors.

Anyway, watch this short video and if you’re not already using this tool, get Clicky!

No Comments »Tags: Clicky, offline media, Web Analytics

If you like tinkering with your website, then you have probably heard of A/B or multivariate testing. This is where you can quickly test new things on your website, such as copy, images, call-to-action buttons, placement, etc., and see which combination effectively leads to more conversions. A/B testing is essentially testing two versions against each other that could be completely different, where as multivariate testing assesses multiple areas of the page and tests all possible combinations. So, if you had 3 versions of a headline, 3 versions of an image, and 3 versions of a button, you would have 27 possible combinations in a multivariate test.

Traditionally, multivariate testing has been where each possible combination gets equal play; meaning each combination is displayed equally to your traffic. Once a visitor is exposed to one of the test combinations, they are given a cookie so that each time they return while the experiment is still in progress, they will see the same combination. Google Website Optimizer is considered a traditional multivariate testing tool, where their algorithm will determine the winner based on how many combinations you have, and how many visitors is required to statistically determine a winner.  Their model shoots for a 12% minimum improvement in conversion rate at an 80% confidence level.

Now we have what’s called adaptive multivariate testing, which is offered by a company called Hiconversion. What they do is the same multivariate set up, but instead of giving equal play to each possible combination, they only test page combinations that are consistently performing in producing conversions. They claim that their methodology dramatically reduces the amount of traffic required to reach a statistically correct “winner”. This real-time adaptation also reduces the amount of loss leads or sale conversions that a typical test can produce.

Courtesy of Hiconversion.com demo presentation

This is sort of how Google AdWords works when you opt for the “auto-optimize” feature, which instead of displaying your ads evenly, they display the best performing ads more often.

Well, I personally was never a believer in AdWord’s optimization feature. I thought they determined a “winner” way too early, and so I’ve always turned off the optimization feature, and did my own split testing within the ad groups themselves.

I also had the same disbelief for the Hiconversion tool initially. First of all, how could you really determine a winner if all combinations were not played evenly? If one was played more than the other, then of course that combination would win!

So I began to ponder about the mathematics involved with this (I know…that’s what I do). First let me start by saying that I do not know how the Hiconversion algorithm works (I did ask them, but they said they would have to shoot me), so this is just my rationalization.

Let’s imagine that our multivariate test had 100 possible combinations. As the testing starts, each combination gets equal play, or 1%. The algorithm can quickly see which combination is starting to get higher conversion rates until it reaches a point to where it begins to test itself. (Bear with me). So if a few combinations are “starting” to look like good performers, the algorithm might say “OK, you got 5 conversions on 100 plays in X time…let’s see if you can get the same 5 conversions or better for the next 100 plays in the same time period.” If the combination meets or exceeds the mini-test, it moves up to the next “level” where it is now played 3% of the time, where if it doesn’t, and lets say it falls to 4, or 3, then perhaps it stays among all of the other combinations that are tested at 1% play. So the combinations in the experiment keep getting tested in this manner until there are only a few left, where a “winner” prevails. All of this happens very quickly, and in real-time. It’s kind of this survival of the fittest scenario because the combinations that can’t leap into the next levels, actually get played less and less over time, since the ones that are performing are eating up their play time.

Anyway, that’s my take on how it might be working, but again, I didn’t design the tool. My ultimate experiment would be to do identical experiments in Google Website Optimizer and Hiconversion and see if they arrive at the same result. Of course, I can’t be experimenting with all of our clients leads and sales, so maybe I’ll try this on my site one day.

9 Comments »Tags: A/B testing, conversion tracking, conversions, multivariate testing

So often we are concerned with the “big conversion” on the website, like purchasing something, for example.  We call this a macro conversion – it’s your ultimate goal.  But what about other activities, maybe not as valuable, but still worth something.

We forget that marketing is basically broken down into these 3 pieces:

Everyone, including upper management, is zoning in on purchase.  But what about awareness?  Remember the circles of trust graphic?  It’s highly unlikely that many will purchase from you when they don’t know you.

My point:  create micro conversions in the Awareness and Consideration stages and measure them!

Things like entering a zip code, joining a mailing list, or subscribing to your RSS feed.  Now you have a chance to converse with some highly potential, future customers on a permission-based marketing system, versus a interruption marketing system.

Now, assign a value to these micro conversions.  A zip code might be worth $1 to you.  Asking for a zip code is great because it further refines what geo-tracking in Google Analytics can’t do.  Now you know what zip code your visitors are from, so it takes some of the guesswork out of your next direct mail piece.

Use this value to compare to the costs you’ve put into the activity, such as SEO, PPC or even web analytics.  Before long, you will be able to see which activity is driving the most value.

1 Comment »Tags: conversion tracking, conversions, pay per click, PPC, Web Analytics