Occam's Razor 
by Avinash Kaushik
Digital Marketing and Analytics Blog

Excellent Analytics Tip #22: Calculate Return On Analytics Investment!

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Analysts: Put up or shut up time!
This blog is centered around creating incredible digital experiences powered by qualitative and quantitative data insights. Every post is about unleashing the power of digital analytics (the potent combination of data, systems, software and people). But we've never stopped to consider this question:
What is the return on investment (ROI) of digital analytics? What is the incremental revenue impact on the company's bottom-line for the investment in data, systems and people?
Isn't it amazing? We've not pointed the sexy arrow of accountability on ourselves!
Let's fix that in this post. Let's calculate the ROI of digital analytics. Let's show, with real numbers (!) and a mathematical formula (oh, my!), that we are worth it!
We shall do that in in two parts.
In part one, my good friend Jesse Nichols will present his wonderful formula for computing ROA (return on analytics).
In part two, we are going to build on the formula and create a model (ok, spreadsheet :)) that you can use to compute ROA for your own company. We'll have a lot of detail in the model. It contains a sample computation you can use to build your own. It also contains multiple tabs full of specific computations of revenue incrementality delivered for various analytical efforts (Paid Search, Email Marketing, Attribution Analysis, and more). It also has one tab so full of awesomeness, you are going to have to download it to bathe in its glory.
Bottom-line: The model will give you the context you need to shine the bright sunshine of Madam Accountability on your own analytics practice.
Ready? (It is okay if you are scared. :)).
Here's part one, let me hand you over to Jesse…

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Hello my dear, dear friends fighting the good fight of analytics. I felt compelled to write about this topic because I, too, am an analyst to the core. However, I've long felt the unsettling sensation of having a tremendous impact on the business, but still having to fight for attention and resources, and always wondered why that is.
After being an actual analyst for a while, I'm now managing the Google Analytics Certified Partner program, and I now realize that it wasn't just me, our entire INDUSTRY is affected by this issue.
Why is it that we analysts feel like we have some amazing untapped ability that could revolutionize any business we touch, and yet we have to fight to be included in strategic conversations where we could do the most good, and we have to fight not to be ignored when we have something important to say?
Why is it that most analytics departments are constantly under-funded and under-staffed compared to the budget-hogs in Marketing or the herds of tech workhorses in IT?
I would venture to say it’s because we’ve made an awfully poor case for the value of what we do. Businesses, by and large, don’t understand the ROI of analytics… the Return on Analytics, if you will.
Everyone else seems to get an ROI calculation, but not us. Marketing dollars (hopefully!) get measured by their Return on Ad Spend. Product improvements are quantified in incremental sales. Even internal tools are evaluated by work hours saved. Yet the analytics team rarely has its costs measured in terms of impact on The Company.
‘But we measure (and hopefully, improve!) the ROI of other things’, you say. 'The impact of analytics is the impact we have on other teams.'
Exactly! And therein lies the problem! The absolute best case scenario is that we spend all our time making everyone else look better, only to let them take all the credit.
Do we really think that if our executives believed that every dollar invested (properly) in analytics would result in ten dollars back for the company, that we would still face the massive hurdles that so many of us deal with daily? Heck no!
However, it’s true, analytics is worth at least 10x what you invest into it. These successes are ours to claim, and it’s high time we started claiming them.
So, what is ROI?
The ROI calculation is cliché and overused because it’s so simple, even a child could do it:

* How much did you invest?
* How much did you make in return?
* Was the latter greater than the former? (And enough so that it was worth the effort?)

With that context in mind, here’s an equation I drew up to quantify your impact as the “Return on Analytics”:

Don’t worry, its bark is worse than its bite. All it’s asking you to do is put the ROI calculation in terms of how analytics works. The formula accommodates for the critical need to compute incremental impact from deployment of an analytics practice.
You see, the challenge with analytics is that you can’t just say “how much did you make in return?” because you were (likely) already going to make something in return. So we have to figure out the impact – the incremental return that you wouldn’t have had otherwise.
So what I’ve done here is:

* Highlight the “full incremental return” within a discrete time unit (such as a day, week, month, whatever) by first subtracting the improved ROI thanks to analytics (Ra) from the original ROI that you were getting before (Rm)
* Then multiplied that impact by the duration of those time units that it will last: (d)
* Finally divide that by the costs it took to get to that impact: Ia

The end result:

‘But it’s so much more complicated than this!’, you argue. Yes. Yes it is. But so is any computation of ROI, if you really want to be honest. What this does is to package your impact into a (relatively) easy to understand way.
Let’s take an example.
Say you’re a mid-sized company who sells hubcaps. Your digital marketing team has a monthly budget of $30k, and the company sees $120k in monthly sales from it. 400% ROI, not bad.
You then hire on an analysis ninja and pay them $5k per month to “fix” your analytics (a bargain, if you ask me), and after 6 months of data-driven improvements to campaigns & landing pages, all of a sudden the same marketing costs are bringing in $180k in sales per month, a success rate which continues on for 12 months (until a new line of hubcaps come out).
To summarize: Six months of effort, twelve months of success (/gain).
Clearly some of the credit for this goes to your marketing team. But before you jump to “my marketing is now making a 600% ROI, that’s fantastic!” and then promptly give the Marketing team more money, it is important to realize that none of this would have happened were it not for the analyst who took the holistic approach to identify the optimization opportunities.
So, let's go back to our formula (above). Punch in some of the relevant numbers and you'll see this:

Holy guacamole! You’ve hit a gold mine! Your six month analytics driven improvement delivered twelve months of astounding results. If every dollar you’ve invested in this team paid off even half as much, then your company would be the #1 hubcap dealer in the world in no time!
This is the potential power of calculating your ROA. Attributing success where it’s due so that you can fuel the true driver of growth.
Once you’ve taken a hard look at what your investment in analytics (everything from tools to people to professional services) has produced in terms of real business results, ask where you need to invest more in order to get to a positive ROA … and not just a positive one, but the one we all imagine ourselves to be capable of.

______________________________________________________

Simple and amazing, right?
Here's the really key part… Businesses often don't understand the ROI of analytics. In fact it is not uncommon that they often don't even understand what analytics is! Here's the hidden awesomeness of computing ROA: If we can prove that there is ROI, they don't need to understand what we do as Analysts! Just like other professions (say, Accounting – what is it that they really do? :)), the analytics practice, and Analysts, will earn the right to be left alone to add value because in a very compelling way Businesses and leaders, through ROA, will know that we are adding value!!
Yes. I hear you (and Jesse acknowledged this as well).
This part of the blog post is to deliver the specificity that you've come to expect on Occam's Razor. Practical examples and specific guidance that will give you a leg up if you are convinced that bringing accountability to your analytics effort is a good thing.
The guidance is going to come to you via a customizable model in a handy dandy spreadsheet. So to speed up your ROA computation, download: Return on Analytics Calculation Model.
The model has a summary tab, a tab full of awesome specific guidance on how to compute incrementality with pitfalls and caveats, and finally a whole bunch of tabs with sample computation of incrementality across various analytical efforts.
Let's walk through the model in detail.
Tab one contains the model for an actual client from whom you can find inspiration. The first thing you'll notice is that the formula has already been created for you. No need to touch this.

The second key element is the annual revenue for your company prior to the implementation of analytics (or a major expansion of your analytics practice). We are trying to establish a baseline. Type it in.
The third element is to calculate the total cost of ownership. Your cost! Ok, ok, you plus the hardware, software, army of consultants and BFFs. :)
Here's what you'll see for that element when you open the model…

The numbers are realistic but by no means reflect what they might look like in your company. I've typed in as many things as I could think about connected to having a web analytics practice (i.e. Total Cost of Ownership).
So say you have Adobe's SiteCatalyst. You have a fixed fee you have to pay. You have a variable cost. You have a hourly support contract. You have an external agency helping you with implementation and online support. You have other software deployed, like tag management (all in vogue now and you know what, it costs money!) and specialized PPC tools and email or other software.
It also includes the important bits, ones we often overlook when creating an analytics strategy: The cost of people inside your company whose primary analytics job is implementation/IT (tagging, retagging, etc.), people whose primary job (greater than 70%) it to provide data but without insights or recommendations ("reporting squirrels," a necessary expense in any large company) and finally people whose primary job (greater than 70%) is to do analysis (and hence not data puke but provide insights and recommendations only).
And the $50,000 for IT resource and $25 for an analysis resource is just a joke I desperately hope is not true in your company (big or small, remember the 10/90 rule for incredible digital analytics success).
Not every single one of these rows will apply to your business. Say you use Yahoo! Web Analytics, the first two rows disappear, the third might not apply, but the rest might. Say you are a medium-sized company using WebTrends or Omniture, the first two rows might not be 100k/50k rather be 1,000k/350k. If you are a larger-sized company, well, you know the drill. If you are a large company you might have an army of consultants, if you are a small business that might be the free time you are getting from your cousin Ali.
So adapt the model, type in your actual costs. Calculate your digital analytics total cost of ownership. It will be revealing. I promise.
Then comes the magical part. What does your company get for all this investment?
The structure is simple, you identify the change you drove and then identify bottom-line impact of the aforementioned change after implementation of your data-influenced recommendation.
Here's what the various bits of impact look like the ROA computation model you've downloaded…

There are literally n number of things you could be driving inside your company.
In the model there are three clusters: 1. Media Optimizations 2. Content / Website Optimizations 3. Product / Company Optimization.
In each case, as you'll note above, there are examples of the type of activity that data might have informed and an example of the incremental impact.
By the way, incremental means incremental. The analytics team found an insight via their data analysis (at this moment you'll really, really regret if the primary function of your analytics practice is to data puke), that insight bundled with a specific recommendation for action was communicated effectively to the senior management, they in turn ensured it was implemented, and revenue went up.
At this point let me say something immensely important. We (Analysts) are NOT trying to claim credit for the entire uplift. We found the insight in the data and recommended an action, but many people are involved from that point on. Your marketing team went and got it implemented. Your copywriter created new copy. Your designer created new graphics. And so on and so forth. We are not trying to say here that we were singularly responsible for the incremental revenue.
We are just trying to say that that incremental revenue came from an insight produced by data analysis. So we are trying to give credit to the data. We are NOT trying to steal credit or undermine the team effort it takes to get things done in every company.
I sincerely hope that this section of the model serves as an inspiration of sorts for the vast net that data can cast in terms of driving change.
You'll see reduction of checkout abandonment rates from quantitative analysis, you'll see impact from improving task completion rate from qualitative analysis (which might drive offline conversions), you'll see impact from technical improvements, you'll see impact on the company's long-term value by improving brand perception or social media presence.
Let your mind roam wild. Look in every nook and cranny. And if your analytics practice is not focused on everything listed in this section (why not?), there is a lot of upside for you!
At least at the moment, not all the rows will apply to your business. That is ok. Fill out the ones that do. Improve over time.
Right now you are surely wondering: "Wait, what about that incremental bit? You ran over that pretty fast. That is hard stuff! "
: )
No. Did not forget that!
First, identifying incrementality is an incredibly difficult challenge. While getting perfect answers is nothing short of a life time effort, getting a good enough answer does not have to be very difficult.
So why not start there?
In the model you'll be delighted to discover a number of examples of how to compute incrementality. For example here's a screenshot of identifying incremental impact from your email marketing program.

The first thing you'll notice is that you can do this exercise in layers.
You can start with something simple. Let's say the analytics team does analysis of current email marketing metrics and identifies improvements to how your company structures the emails that go out. The recommendations are implemented and that drives an additional 100k clicks from the email campaigns. Assuming that nothing else was changed, it is now easy to measure the incremental impact of these changes.
Or maybe nothing was changed in the campaigns, but conversion rate was improved from 2% to 5% by changing the checkout conversion process for email campaigns. Well, it is easy to calculate that impact.
Or maybe you have an advanced analytics team with lots of senior management support and are able to improve the email copy and calls to action, the checkout process and do much better cross-sells and upsells and improve average order value. Well, that third cluster shows you how your computation might look.
Is it a perfect approach? Almost. Does it get you going in the right direction? Emphatically, yes!
As Voltaire put it: "Le mieux est l'ennemi du bien." (The best is the enemy of the good.)
There are other examples in the spreadsheet that should serve as guidance/inspiration for approaches you can take when you compute incrementality of the impact you deliver via your analytics practice.
Here's the section on computing value delivered by your investment in software to do multi-channel attribution modeling and the person you hired specifically to do that work…

From an impact computation perspective you can see how brutally simple the process is. Either you delivered revenue increase, or you did not.
Multi-channel attribution modeling is not easy. It has an astounding track record of failure. Identifying which model to use to attribute credit for a single conversion across multiple media channels is immensely difficult. Yet calculating whether it improved the bottom-line, whether it delivered positive ROA, is simple. You fill out the blue cells. You look at the row called Incremental Revenue. If there is something there, your digital analytics investment is worth it. If you have nothing there … well, you know … let's figure out how to say data is always worth investing in. :)
There are a few more examples I wanted to insert to really make this concrete. We cover how to compute incrementality from improving conversions, but also how to do that for the micro conversions and capture the impact of the long term impact on the business by tracking micro conversions.
Here's an excerpted version of that section…

Excited? I hope so. I was giddy as a teenage school girl just creating these for the model!
There is also a tab to help you identify the incrementality from landing page optimization, and from improvements you make to the cart and checkout process. (You know my obsession with both, see best digital marketing experiences post.)
And we can't do anything related to data driven improvements without helping you compute the incrementality from insights we identify for our Paid Search campaigns.
I'll let you be delighted about both those tabs when you look at the model, and not spoil your surprise by posting images here.
The model contains one last present for you. Checkout the tab titled General Impact Analysis.

If you are new to the field you are perhaps wondering what kinds of actions you could be taking for each focus area (PPC, Email, Display, etc.). You'll find that in this tab. Column B provides description and examples of the types of outcomes you might drive in each initiative, Column D sheds light on the implementation difficulty of various types of analyses, Column E helps you understand the difficulty you'll face when computing incremental return and finally a reality check under the column titled validity of incremental return .
You are now all set to go!
Here's the link again: Download: Return on Analytics Calculation Model.
Closing Thought #1: "I ain't got no incrementality!!"
It is entirely possible that at the end of looking at all the tabs in the spreadsheet you have nothing to type into the ROA computation model proposed by Jesse. A likely reason for that is that you were unable to identify any action taken as a result of your analytics practice.
There might be a simple causal factor for that. Your analytics practice is focused on DC and DR. And it turns out that you need to obsessively focus on DA for your analytics practice to have an impact on the company's bottom-line.
DC, DR & DA are three key components of any analytics practice. Data capture, data reporting, and data analysis.
I discussed this framework extensively in a recent blog post: Web Analytics Consulting: A Simple Framework For Smarter Decisions.

As you'll note in the DC, DR, CA framework post, most analytics efforts (especially web analytics), consulting or in-house, are focused on collecting ever more data and in figuring out how to puke an ever-increasing amount of it in the form of standard reports via as much automation as possible. Sadly this rarely leads to the recipients gleaning any insights. Which in turn ensures that the organization is data-rich, but action-poor. Which, heartbreakingly, does result in zero actual impact on the company's bottom-line.
Hence your inability to type anything into the column titled Incremental Revenue/Impact.
So if you don't have anything to type into the various tabs in the spreadsheet I encourage you to read the DC, DR, DA post for specific guidance on what is contained in each area and how to ensure you have a better balance (egregiously focused on DA) for your analytics practice.
More investment in analytics (and your salary) will come from an ability to clearly demonstrate impact on the bottom line; otherwise, we will remain third-class citizens of the business world. The model outlined in the spreadsheet could possibly be a diagnostic tool in helping identify problems with your analytics practice (big data or small data) and figure out how to create a practice that is focused on ensuring incremental impact.
Closing Thought #2: Inspiration wrapped inside an exhortation!
You'll fail to attract investment in analytics inside your company (and a higher salary for yourself) if you are unable to show an impact on the company's bottom-line. You'll fail to show an impact on the company's bottom-line if you don't recommend actions your executives should take. You'll fail to recommend actions without an obsession on analysis of data. And yes, you'll fail to analyze data without collecting it.
If your analytics practice is not producing any actionable insights (hence no ROA) then it might be because the analytics practice is not focused on what's important to the business (advice: Biggest Mistake Web Analysts Make… And How To Avoid It!), or focused on reporting and not analysis (advice: Difference Between Reporting And Analysis), or perhaps needs a crash course in how to do better analysis (advice: Beginner's Guide To Web Data Analysis), or perhaps just needs to extract more value from the tool you have (advice: Google Analytics Tips: 10 Data Analysis Strategies That Pay Off Big! ). Identify and fix the problem. Promise me you are not going to settle for a lower salary and a boring job!
I wish you all the very best.
Before we go, my deepest thanks to Jesse Nichols for contributing to this post and inspiring a discussion that has been a long time coming.
As always, it is your turn now.
Does your company compute the incremental impact of its big data, digital analytics efforts? Is there a part of your effort that you are able to identify incremental impact for most easily? What are the biggest challenges you've faced to justify return on analytics? The model is centered on ecommerce/digital type businesses, what unique challenges do you face as a non-ecommerce/non-primarily-digital business? Do you have suggestions for improvements to Jesse's ROA formula? What are some salient hidden dangers we might be overlooking?
Please share via comments.
PS: An Ask from You: I feel that the model could use more tabs of incremental computation guidance. Can you help me create more tabs for various online or offline marketing initiatives powered by analytics? If yes, could you please create additions and email them to me? I'll be immensely grateful, and I'll add it as a tab to the model in this post (and of course credit it to you in the model, with a link to your blog / twitter profile / company). Please consider helping the community.
Thank you.

Koozai

UX, CRO, SEO: What Does It All Mean And Where Does It All Come Together?

by Ned Poulter on 12th December 2012

Ned Poulter looks at where the line falls between UX, CRO, SEO and many other web design disciplines whilst ultimately asking how you can leverage all of these aspects as somebody working in SEO.

Usability = SEO

The lines between UX and SEO are becoming increasingly blurred. Largely this is because many SEO techniques are now also in-line with UX best practice; they go hand-in-hand. Many of us have been aware of this mutually beneficial relationship between SEO and usability for a long time but have chosen to pay little attention to the finer details, either the client’s budget doesn’t cater for it or there are more important changes taking place and UX changes fall by the wayside.
Some top SEO companies like SEOGadget, Distilled, Seer Interactive and Koozai have naturally begun to offer UX and CRO services to complement their existing client offering, the reason for this? The skills to offer this were often already in-house and by optimising the entire process of website conversions, more so than simply getting traffic to the site, this allows us to expand upon the remit of traditional SEO and branch into user experience and CRO and ultimately, help our clients’ make more money. This post will explore the crossing of boundaries between the disciplines, and will aim to provide you with:

• An insight into approaching these for best practice
• How to communicate SEO changes in terms of user experience improvements
• A number of recommended UX/CRO tools that can be utilised to improve user experience on your site

Google <3s Good UX

When you look closely at some of the algorithm updates over the last 12 months, specifically:

• Page Layout Algorithm change (read more here)
• Google ‘Venice’ update – serving more geographically appropriate results based on your location (more here)
• Even the debate on how page speed is now being using as a quality signal and improvements can help improve a site’s ranking (something that Gianluca recommended in this post)

Taking these updates into consideration you start to realise that ultimately Google’s goal is ensuring that their index consists of the best results on the Internet, both in terms of relevancy and also user experience. If Google serves a website that offers a bad user experience causing a user to go back to the SERPs and ‘try again’, then that reflects badly on them; to Google this can be a vicious cycle and ultimately they want to avoid this!

Communicating SEO without mentioning SEO

One issue that many SEOs are commonly faced with is the inability to communicate why site optimisation recommendations should be applied in terms that the client or developer, can understand. SEOs, more often than not, need to drop the jargon and speak to them like a human, one way of doing this is to describe your recommendations in terms of improving user experience, clients can relate to this. How many times have you found yourself in a situation where even before making the recommendations a client is already looking cross-eyed and is baffled by the mentions of ‘XML sitemaps’, ‘linking root domains’ and ‘robots.txt files’?
I’ve found great successes when working with clients in approaching SEO a bit like an academic discipline, starting a site audit with a series of presentations that I dub ‘SEOSchool’. However, I’ve found that with some clients this doesn’t always resonate, they are time-pressed and more often than not simply don’t care, it’s a bit-part of their overall marketing budget and, after all, worrying about this is what they’re paying me for! So you persevere, make your recommendations, see the on-site optimisation take place, begin your day-to-day of SEO work, site traffic begins to rise and results start to materialise. Next you get a call from your client, you’ve now got their attention and they want to know what you have done to make that happen. Sound familiar? We’re back to square one…
I’ve been in this situation a few times now and personally have found that more and more that when communicating with some non technically-savvy clients SEO is best explained by focusing on how many common SEO fixes for a site are simply a process to create a better user experience. I’d urge you to do the same. Next time you’re trying to explain certain SEO changes to a client or developer, consider approaching the explanation in a slightly different way, like highlighting potential gains like for every 1 second of load time, conversion drops 7%.
Below I have identified several areas that I have found SEO and CRO techniques can be employed in tandem, including mentions of notable tools that can help you do this…

Optimised Page Titles & META Descriptions: Include Relevant and Clear CTAs

This actually lends itself to a conversation I’ve had with a number of SEOs lately regarding optimisation of page titles and META descriptions, and how ‘old school’ examples are dirtying up the SERPs:

• They completely fail to deliver a good user experience to the end user
• It offers little to no information of what the page contains
• Contain no call-to-action
• This can actually have a more negative effect than positive

While not the worst I’ve seen, consider the example below for a search for ‘cheap car insurance’, More Than Insurance are trying overly hard to optimise their homepage:

• Truncated page title
• Use | of | piping | to | separate | keywords
• Confusion through attempt to target multiple keywords

However this would be much better:

• Clear call-to-action in page title
• Convincing persuasive language in META description
• Use of ‘today’ adds immediacy to call-to-action

Many SEOs are turning to others to help write their page titles and METAs, focused on including convincing sales-orientated language with prominent call-to-actions for the user. Try this yourself; once you’ve identified your target keywords, try giving the role of writing page titles and META descriptions to your sales team, or even your PPC team.
Tip: I’d strongly recommend using SEOMofo’s Snippet Optimiser tool to test and visualise recommendations.

Split Test, Then Split Test Again, Then Split Test Again…

Writing page titles and META descriptions in the way identified above is just a start, consider the full journey your user takes through your website once they have reached it. Split testing page titles and call-to-actions allows you to test and iterate to create the optimal experience for your users. There are a multitude of tools out there to help you do this, but I’d certainly recommend looking into three that are incredibly affordable:

• Optimizely
• Visual Website Optimizer
• Google Content Experiments (formerly Google Website Optimiser).

Don’t see how this can help? See this example from Highrise where they increased conversions by 30% simply through using Google Content Experiments (formerly Google Website Optimiser).
Worst performer in test

Conversion increase of 30%

Pay Attention to Information Architecture

Information architecture is a fundamental building block of user experience on your site, ask yourself:

• Can individuals find what they’re looking for easily on your site? 
• How were your top-level categories selected? 
• Did you ask your website visitors/test to form this decision on top-level categories? 

While often overlooked, URLs are a classic example of signposting for the user. Think how many times you refer to the URL in SERPs, or glance at the URL bar in your browser to help you understand where you are on the site. Changing URLs can be an arduous but very rewarding process. Follow simple rules for this and ensure that they:

• Maintain consistency
• Support site structure
• Are intelligible to humans

Information architecture is a vitally important aspect of your website, without a rigorous testing process some areas of your site may simply not be discovered by users. There are a number of tools to help test your information architecture, below I’ve recommended some of the best:

• TreeJack - ‘Information architecture validation software’, allows you to test your information architecture without visual distractions.
• Usabilia - Acquire feedback on you site layout and information architecture even when it’s in design/wire-framing stages.

Gather Feedback, Constantly Iterate

Listen to your customers, constantly test and iterate based on the feedback you receive. There are simply hundreds of tools out there to do this, but consider the following tools to approach this:
On-Site/Page Feedback

• Qualaroo - On-page feedback, try asking purposefully broad questions like ‘what one thing would you change about this page’
• Olark - On-site live chat, helps you rectify issues users are having when navigating your site and help them to complete their conversions.
• 4Q - Customer feedback

Session Recording
Recording your user’s journey will allow you to understand better how they are navigating the site and to identify areas of potential improvement, recommended tools:

• Camtasia
• Silverback (Mac only)

Crowdsource User Feedback
Much like the on-site/page feedback, you can open this up in a broader way using these tools:

• WhatUsersDo
• UserTesting.com
• FeedbackArmy
• FiveSecondTest

Good News! You’re Probably Already Doing It

As marketers, our job is focused on influencing people’s opinion based on an understanding of their needs and wants. Improving user experience helps to remove instances where individuals get frustrated online, which in turn can have a negative effect on your brand as a whole.
The good news is you’re likely to already be aware of this, you just need to secure some time and resources to focus on user testing, split testing and iterating based on this feedback. Trust me, you will not be disappointed. I predict that in 2 years time the best SEO agencies out there will have flourished through offering CRO services and conducting user testing, make sure you don’t miss the boat.
To finish, I could not put it better than StateofSearch blogger Gianluca Fiorelli pointed out in his article ‘What is Google all about now’ (referencing Google’s own company philosophy):
“Focus on the user and all else will follow…”
The views expressed in this post are those of the author so may not represent those of the Koozai team.
Image Credit:
User Experience Wheel and User Experience from BigStock

• inShare9

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Ned Poulter

Ned Poulter is an enthusiastic and passionate SEO, currently working as the SEO Manager for Quirk London. Ned is a familiar face at SEO conferences across the UK, can often be found discussing SEO and digital marketing on Twitter, as well as blogging for State of Search.

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Las Pequeñas empresas encuentran el ROI en el Social Media. #Infografía #ROI #socialmedia.

Magenta Innovaciones C.A.

Las Pequeñas empresas encuentran el ROI en el Social Media #Infografía #ROI #socialmedia

por Verónica Maria Jarski   |  Traducido por: Adriana González H.

29 de mayo 2013

Antes de empezar a leer el artículo, me gustaría dejar una pequeña definición para aquellos que se estén incursionando en este maravilloso mundo del Social Media:

¿Qué es ROI?

ROI son las siglas en inglés de Return On Investment y es un porcentaje que se calcula en función de la inversión y los beneficios obtenidos, para obtener el ratio de retorno de inversión.

Para que se entienda mejor es  uno de los conceptos que tenemos que tener en cuenta a la hora de evaluar una inversión en un negocio, tanto online como offline. El ROI, el retorno de la inversión, que ahora -en tiempos de crisis- todavía cobra mayor importancia, para saber si estamos gastando bien nuestro dinero en nuevos negocios, o realizando nueva inversión en negocios que ya tengamos funcionando.El ROI es un valor que mide el rendimiento de una inversión, para evaluar qué tan eficiente es el gasto que estamos haciendo o que planeamos realizar. Existe un fórmula que nos da este valor calculado en función de la inversión realizada y el beneficio obtenido, o que pensamos obtener.ROI = (beneficio obtenido – inversión) / inversiónEs decir, al beneficio que hemos obtenido de una inversión (o que planeamos obtener) le restamos el costo de inversión realizada. Luego eso lo dividimos entre el costo de la inversión y el resultado es el ROI. El valor de ROI es un ratio, por lo que se expresa en porcentaje. El ROI es un parámetro muy simple de calcular para saber lo positiva que sea una inversión. Los valores de ROI cuanto más altos mejor. Si tenemos un ROI negativo es que estamos perdiendo dinero y si tenemos un ROI muy cercano a cero, también podemos pensar que la inversión no es muy atractiva. A la hora de evaluar una inversión nos viene muy bien calcular el ROI, sobre todo para comparar dos posibles inversiones, pues si con una inversión conseguimos un ROI mejor que con otra, pues debemos pensar en invertir nuestro dinero únicamente en la fórmula que nos reporte mejores ratios.
Si utilizas Google Analytics para tus mediciones, lee este artículo que te podría ayudar : http://www.mentalidadweb.com/2012/03/que-es-roi-y-como-medirlo-con-google-analytics/

Ahora si, vamos al artículo que nos trae la gente de http://www.marketingprofs.com:

Las pequeñas empresas pueden encontrar un retorno de la inversión (ROI) en los medios sociales, pero tienen un duro medio con es Facebook.Un nuevo estudio de  Manta ofrece información de más de 1200 propietarios de pequeñas empresas con respecto a sus principales preocupaciones. Manta creó entonces la siguiente infografía de sus hallazgos.El estudio reveló que la participación de los medios sociales es cada vez mayor entre las pequeñas empresas. “Casi el 50% de las pymes ha aumentado el tiempo dedicado a los medios de comunicación social digital, en comparación con hace un año”, dice Manta. “Más de uno de cada tres propietarios de pequeñas empresas dedican entre una y tres horas a la semana a la gestión de sus canales de medios sociales digitales, mientras que el 10% gasta más tiempo.” Para las pequeñas empresas, la adquisición y la participación de nuevos clientes es el objetivo principal de la utilización de medios de comunicación social digital, dijo que 36%. Ganando nuevas vías de concurrencia y referencias (19%) fue el segundo.
Otras conclusiones relativas a las pequeñas empresas y los medios de comunicación social digital son …

• 18% mencionó a Facebook como plataforma de medios sociales más difíciles de mantener.
• 53% de las empresas dicen que tienen una persona dedicada a actividades a los medios sociales en la empresa.
• 39% de las empresas dicen que ven un retorno de la inversión (ROI) en sus actividades en los medios sociales.
• 79% de los propietarios de pequeñas empresas son optimistas sobre sus perspectivas de negocio en el segundo trimestre del 2013. Y seguirán invirtiendo.

Para más información sobre las conclusiones de Manta, echa un vistazo a la siguiente infografía.

Veronica Maria Jarski es escritor senior de MarketingProfs y editor de la MarketingProfs blog diario Fix . Llegar a ella a través de veronicaj@marketingprofs.com .

Measuring Social Media ROI With Google Analytics

Measuring Social Media ROI With Google Analytics

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Social media is an integrated component of so many companies' marketing strategies, but very few of us are tracking the ROI of our social initiatives. Since Google Analytics has released social media reporting, it has streamlined the way we can report onsite social media conversions and value.

In this post we will cover best practices for ensuring you have accurate and actionable data inside Google Analytics and also step outside of the tool to complete the full picture and establish onsite and offsite metrics to help us report on our success and most importantly, drive action.

Below is a quick video where Justin Cutroni, Analytics Advocate at Google, and I share some ideas on Social Media measurement, just to open the appetite!

Measurement Challenges: Multiple Data Sources and Offline Impact

There are a number of challenges we encounter when trying to measure and report on our social media initiatives. Our first challenge is that the majority of interactions don't actually occur on our website and instead happen on the individual social network. For example, when somebody 'likes' our content on our Facebook page we can't get this data into our Google Analytics reports.

This leads to our next challenge which is aggregating data from all these different data sources in order to report on performance and perform analysis. For a small business this could mean manually grabbing data from the different social networks and working in Excel or a Google Spreadsheet, but for larger companies this would become a debilitating process.

Our third challenge is to understand the offline impact of our social media campaigns. What do we do if someone ends up purchasing in-store? How do we understand the value of a phone call? Or what if someone tells a friend or colleague about our brand after seeing a post on a social network? These are much harder questions to answer.

Data Collection: Tagging Social Campaigns

Before we look at reporting we need to start by taking a moment to ensure we have the best possible set of data available. You will need to ensure you are using Google Analytics campaign tags to correctly track people who are clicking through to your website from your social media campaigns.

For paid social ads or promoted posts, my recommendation is to always set the campaign source as the domain of the social network. For example, for Facebook we would use facebook.com and for LinkedIn we would use linkedin.com as this is what you will already see appearing inside your traffic sources reports. I would then always set the campaign medium as social. Next, you will need to define a campaign name to distinguish the particular paid social network campaign you are running and you can use content to report on the ad variation or call-to-action people are clicking on to then travel through to your website. For example:

It is best to leave the term blank when creating your campaign tagged URL as this can potentially show up in your keyword reports. You will also want to change the content for each ad variation you are running and the campaign name to suit your reporting needs.

You should also consider using campaign tagged URLs for your organic posts on social networks. This is because when someone clicks through to your website within a social network app, like the Facebook app on your phone, the visit will be seen as direct traffic instead of being a referral from Facebook. This means you could be missing a large portion of your social network traffic inside your Google Analytics reports. To tag your organic initiatives you can use a similar tagging method, but change 'social' to 'referral' in the example above.

Getting Your Data: Social Data Collection and Reporting Tools

Now we have tracking in place for our website and we can see data for all of our inbound social network traffic we need to look at pulling together data from our website and importantly from the individual social networks too. Lets look at a few options for getting all of our data.

The first option is going to be the most painful and that is to manually log into each social network and make use of the data they make available to us. For example, we can head over to our Twitter account to find our total number of followers and browse through our posts to find ones that were retweeted and received comments. We can also head over to Facebook Insights and export data for a particular time period. However this is not practical and with Twitter we are actually missing data about how many clicks our posts have received and we can't select a data range for reporting. So that isn't a very good option.

Now we need to look at tools that can pull all of this data for us. There are a huge number of options ranging from expensive to accessible. My preference is always tools that are easy to use and get the job done quickly and these tools are also generally cost effective too.

1. Hootsuite is a social management tool that also allows you to report on your social media initiatives. Hootsuite integrates with Google Analytics, but unfortunately the reporting on individual posts is limited and does not include the reach (total audience size) of your posts.
2. Simply Measured is a reporting tool that allows you to pull together data from different social networks and from your Google Analytics reports. You can access reports online or using Excel. The solution is flexible, but does start at $500 per month, so might be restrictive for smaller organizations.
3. Sprout Social is another social management tool with a more complete set of integrated reporting and also includes integration with your Google Analytics reports. Sprout Social allows you to quickly create a report for a given time period for all your posts for a particular social network. The report includes clicks, responses (including replies, comments and shares) and reach (audience size). It's certainly not perfect, but it is an accessible tool that will help you be in control of your social network data.
4. Buffer is a tool that allows you to schedule your social media posts. It is a simple tool and doesn't provide a full set of management features, but Buffer does make individual post analytics available. Unfortunately, you can't export the analytics to easy aggregate the numbers, but you will find the potential reach of each post and engagement metrics like clicks and retweets for each post you have published.

The options we have looked at so far give us access to our organic social media data, but what about our paid campaigns? You can look towards enterprise-level solutions for aggregating paid and organic data, but grabbing data from our paid campaigns is fairly straightforward and more importantly available via the major social networks. For example, you can download your advertising data from Facebook, LinkedIn and Twitter with very little effort.

Tip: Once you have downloaded your advertising data you should consider uploading the impression, click and cost data into your Google Analytics reports using Cost Data Upload, but this is a topic for another post as we will focus on pulling together all of our data outside of Google Analytics.

This of course brings me to Google Analytics. We need to extract our onsite data for our social network traffic together with our goal conversions and any ecommerce value we are tracking. Before we really dig into the data, lets look at the metrics that we can use for reporting and analysis.

Metrics That Matter: Actionable Social Reports

There are a number of different metrics you can use to report on various aspects of your social media initiatives. I encourage and urge you to not use every single metric I will cover here, but instead focus on the few that help you drive action to improve your campaigns and drive greater value for your website.

Branding Metrics

For purely branding objectives you might report on number of posts and audience size, but this is boring and definitely not actionable. Consider expanding on these metrics by including posting change rate where you calculate the percentage change based on the number of posts you are creating in a given month. This can then be compared to audience change rate where you calculate the percentage change in your audience size. This will allow you to quickly see if an increase in posts leads to an increase in audience.

Engagement Metrics

To report on engagement you might report on the total number of people liking your posts, but you should really focus on metrics that help you drive action. Start by reporting on the conversation rate for each post, this is where you divide the number of interactions by the audience reach for each of your posts. By identifying your posts that generate the highest conversation rates you can use these topics to guide your future posts and tailor content to what your audience enjoys. You can also report of the total number of conversations, mentions and shares you are starting to paint a more complete picture of how people are engaging with your content.

To better understand your overall engagement with your audience you can report on audience churn rate to see the percentage of your audience that is leaving your social networks. By segmenting your audience churn rate by individual social network and correlating churn to particular posts or post topics you can help shape your future posts to ensure they are appropriate for your different social network audiences.

To understand how social networks are leading people to your website you can report on the total number ofsocial network visitors to your website. Consider adding social network visitor growth rate to easily compare your other social media metrics and identify if changes are resulting in a trickle down effect to your website. For example, you will be able to compare your audience change rate to your social network visitor growth rate to see if you are having a positive impact in driving visitors to your website.

Conversion Metrics

To report on conversions resulting from your social media initiatives you need to ensure you are correctly tracking the inbound links directing people to your website. From here you can use Google Analytics to report on your social media conversions and by using the campaign tagging method we covered previously, you will be able to split your paid and organic efforts when reporting.

We should all be reporting on the total conversions occurring onsite and the value of these conversions. If you haven't already established values for your conversions, then you will need to take the time to do this, I recommend reading Avinash's post on identifying values. This will allow you to report on the direct dollar value of your social channels.

There are also methods for tracking offline conversions that are being driven by social media, including coupons and dedicated phone numbers. To keep this post on track, we are going to focus our attention to online conversions, but once you have your offline tracking in place you can simply replace or supplement your offline conversions and value with your online conversions.

Crunching The Numbers: Establishing Social Value

In order to calculate the dollar value of each of our audience members we are going to use Dan Zarella's formula for calculating the value of a like. This allows us to use our conversion data to calculate an average potential value for each of our audience members. Here is Dan's formula:

L / Upm x (LpD x 30) x (C / L) x CR x ACV = Value of a Like

Where:

• L is Total Likes
• UpM is Unlikes per Month
• LpD is Links per Day
• C is Average Clicks per Post
• CR is Conversion Rate
• ACV is Average Conversion Value

In essence we take our onsite conversion data and combine this with data about our social network audience. This allows us to define a value even if people don't click through to our website. Then using this value we can calculate the ROI of our social media channels.

Social Media ROI Reporting Template

So you don't have to create your own spreadsheet you can use the one I have developed to speed up your social media ROI calculations: http://goo.gl/EByA4. You will need to enter some data for each of your social networks and from there it will automatically calculate your ROI.

Tip: If you are struggling to fill in the data, head back to 'getting your data' in this post for some tips on getting your social network data.

Now you can see the ROI of each of your social networks. Great! The spreadsheet includes a 'Total ROI' section where you will see ROI calculated based on your total audience. There is also an 'Incremental ROI' section where ROI is only calculated based on the new audience members you have acquired for the period. This gives you some flexibility on how your report, some of us might consider our investment as part of social media retention, while others might be more concerned about driving audience growth. Choose a section that best fits with your strategy and style of investment.

Get the Social Media ROI Reporting Template

Factoring in 'Friends of Friends'

If you are running ads on social networks you can also use this data to help factor in the effects of your content being shared and your brand being mentioned by your audience. This allows you to establish an approximate value of your 'friends of friends'.

Start by identifying the total audience size of a recent paid campaign you have run. For example, if you ran a Facebook campaign you will be able to find the campaign reach, which is the number of people who saw your ads. You will also have the number of page engagements. By dividing the number of page engagements by the campaign reach you can calculate the engagement rate, which is the percentage of the audience that engages with your page and page content. We can then apply our paid engagement rate to our 'friends of friends' to roughly calculate the number of people we can add to our organic audience.

This is certainly not perfect, but it is a good starting point to help us establish a value for our extended organic audience. Ideally the paid audience data you use for the calculations would have similar characteristics as your organic audience, for example their interests and other demographics. In a perfect world we would also only use page engagement data from our paid campaign that results in likes. If you don't have a large enough campaign, then go with the data you have available, this might include people viewing photos and other less valuable page interactions.

Let's say you have calculated your paid engagement rate and find that it is 0.052%. You can then head over to Facebook insights (or your tool of choice) to find your total number of friends of fans. If you have 500,000 friends of fans and an engagement rate of 0.052%, then you have the potential to add an additional 260 fans to your audience. Now you can take the average value of an individual audience member and multiply it by the number of potential fans to find the additional audience value of your 'friends of friends'.

Further Analysis

Now that we have established an ROI figure for each of our social channels you can begin to focus on improving your results by allocating your resources appropriately. In order to turn your analysis into action you should also begin to explore your social media efforts in more detail by performing content analysis for your individual posts.

Content analysis will enable you to understand the post that are most engaging and most successful at driving value, so you can repeat what works to more effectively leverage and grow your audience. Consider analysing your content by aggregating posts by their theme, tone and content, you can also consider grouping posts that contain links, questions and even different capitalization and punctuation. This will help speed up your analysis and help define the best content strategy for your social campaigns.

Now it’s over to you to start reporting on your social media ROI! I would love to hear your feedback, so please add your thoughts in the comments below.

Related Content

1. The Definitive Guide to Google+ Analytics
2. Measuring Social Media Impact with Web Analytics
3. Social Media Measurement with Google Analytics [video]

Submitted by Benjamin Mangold on April 2013

About Benjamin Mangold

Benjamin Mangold is the Search & Analytics Director at Loves Data, a digital analytics and online marketing agency based in Australia. He lives and breathes Google Analytics. Follow him on Google+ or Twitter.