Filed under: Analytics, Optimisation, Revenue Performance Management (RPM) | Tags: Analytics, Optimisation, Revenue Cycle Modeling
Filed under: #mktgcloud, Datarati, Optimisation, Video | Tags: Optimisation, Video
In this presentation delivered at Stanford, Dan Siroker, responsible for Analytics & Testing at the Obama Campaign, describes how they used data to win the presidential election.
He shares numbers from the online campaign and insights into how to apply Analytics to drive decision making on developing, designing, and marketing a website.
Filed under: #mktgcloud, A/B Testing, Actionable Insights, Behavioural Targeting, Cloud Computing, CRM, Data, Datarati, Email Marketing, Forms, Lead Generation, Lead Nurturing, Lead Scoring, Loyalty, Marketing Automation, Marketing Cloud, Multivariate Testing, Optimisation, Retention, Search, Segmentation, Software as a Service, Technology, Testing, Web Analytics | Tags: A/B Testing, Analytics, Lead Generation, Lead Nurturing, Lead Scoring, Marketing Automation, Optimisation, ROI, Web Analytics
Another open letter to all Australia, New Zealand & the wider Asia-Pacific digital, direct and data-driven marketers.
As we start 2010, I thought it is critical for all marketers to understand the basics of the term ‘Marketing Automation’, as there STILL seems to be confusion in the market as to what the term means, why’s marketers need it, how it works, and what will happen if they don’t start using it.
What does the term ‘Marketing Automation’ mean:
‘Marketing automation’ is the termed used in the industry to describe the use of a marketing automation database to manage and automate the process of converting prospective customers into actual buyers.
By automating the various tasks and workflows involved in demand generation, lead management, and sales and marketing alignment, a marketing automation database contributes to shorter sales cycles, increased revenue, and better marketing ROI.
A Marketing Automation Database allows a marketer to execute and manage the following all in one centralised database:
- Lead nurturing
- Lead scoring
- Lead generation
- Website monitoring
- Email marketing
- Web Forms
- Landing page creation/optimisation
- A/B + Multivariate Testing
- Marketing asset management
What A Marketing Automation Database is Not:
A Marketing Automation Database is NOT a customer relationship management (CRM) database. A Marketing Automation Database is a SEPERATE marketing database that holds all of the above marketing and behavioural data and integrates with a customers CRM database which holds the customer’s sales and customer service and support data.
The term ‘Marketing Automation’ is designed to meet the specific needs of marketers and involves a holistic approach to generating, nurturing, and converting leads into customers by automating a variety of marketing techniques (e.g. email, Website\monitoring, landing page optimisation, and more) and ensuring marketing and sales alignment throughout the process.
(See previous post on Marketing Automation Database vs. Customer Relationship Management Database)
In the last 2 weeks here is a list of questions that I’ve heard from digital and direct marketers and their agencies:
Q. Why should I change? What will happen if I don’t?
Your email marketing, paid search, paid display and web analytics data is all sitting in disparate databases and typically in an aggregate data format. So how can you possible determine what a prospect or customer is doing down to an individual level.
For example, lets say you want to run an email campaign. You segment your data in your email marketing database, dump in your creative and then hit the send button. What comes back is metrics on opens and click-thrus. Where this fundamentally FAILS is that once that prospect or customer clicks from a link in your email to either a landing page or your website you lose complete visibility at the individual level. So now you look at the number of click-thrus from your email blast and compare that with the aggregate web analytics data of unique visitors and assume the spike in traffic is as a direct result of your email blast.
We as marketers should be embarrassed if this is the way we are still measuring the performance of our digital campaigns. Why? Because the technology to do this exists and there are many companies in Australia & New Zealand using it!! Its called a Marketing Automation Database!
So what happens if you don’t embrace it? The Marketer will eventually lose their job or the agency will lose the client as their level of measurement and analytics are not up to scratch with the industry’s best practice.
Q. How does the issue impact my industry? What are my peers and competitors doing?
A marketing automation database is a fundamental requirement for every digital marketer who want to effectively track, score, measure and optimise their campaigns. The companies who use this technology and the actionable data insight to optimise their campaigns will simple produce better conversions and campaign ROI.
A number of your peers and competitors are already using this technology here in Australia & New Zealand producing ROI numbers as high as 4000%.
Q. Are there best practices I can refer to? Which experts can help me think strategically?
Yes, we here at Datarati use our aggregate customer and campaign data insights across multiple industry verticals to provide our customers with industry best practices in Email marketing, Lead nurturing, Lead scoring, Lead generation, Website monitoring, Web Forms, Landing page creation/optimisation, A/B + Multivariate Testing, Marketing asset management and ROI/Analytics.
Remember THIS: Data drives Insight. Insight drives Strategy. Strategy drives Creative. Creative drives Response. Response drives Revenue. Revenue drives ROI.
Q. What are the options or alternatives? Who can add the most value to the project?
There are multiple options on the market today, but one clear winner in the marketing automation space here in Australia & New Zealand but also globally. The marketing automation database vendor leading this charge is Marketo. They added 110 new customers in Q4 2009 alone, dominating the marketing automation category globally. In fact, more companies choose and switch to Marketo than any other marketing automation vendor: http://www.marketo.com/about/news/marketo_adds_110_new_customers_in_q4_2009_dominates_marketing_automation_category.php
Success breeds success. So who is going to add the most value to your project. Quite simply, the stand out leaders in the space.
Q. What if? What if end users won’t adopt the new process?
With any new technology comes the adoption issue. Historically, this issue was very big a few years ago because the marketing automation software vendors that existed back then had developed user interfaces that were very difficult for a marketer to navigate through, thus creating an adoption problem.
What we’ve seen change dramatically in the last 12 months is new marketing automation databases on the market like Marketo who’s user interface is by far the leader in usability as well as functionality.
Lastly, with any new implementation change management is critical. Therefore, regardless of what type of solution you end up selecting it is critical for the vendor or their partner to provide you with a change management plan and approach to ensure success.
Q. Why should I trust your company? How long will it take me to get an ROI?
You should trust the company and the team that has the most experience and successful track record in this space.
Results will always speak for themselves.
Your ROI can be acheived within 1 email campaign as we recently saw with a customers first email campaign. There first campaign generated such a high ROI that they were able to pay for the marketing automation database for the next two years.
Are you ready to get started?
These types of results are awaiting you…
Give us a call to arrange a meeting!
Datarati Pty Ltd
Level 1, 111 Elizabeth Street
Sydney, NSW 2000
Marketing Automation & CRM Director
Datarati Pty Ltd.
Level 1, 111 Elizabeth Street
Sydney, NSW 2000
Filed under: A/B Testing, Actionable Insights, Datarati, Multivariate Testing, Testing | Tags: Conversion, Optimisation, Tips
Here are 31 fantastic optimisation tips from the Widerfunnel Conversion Optimisation Blog.
- Have you tested your Call-to-Action on right vs. left side of the page?
- What are the top 3 components of your Value Proposition? Are they immediately obvious on your landing page?
- Have you tested adding credibility indicators to your website; testimonials, reviews, awards, stats
- Can your landing page be any more specific? Can you drive to a product page instead of category page?
- How can you reduce Distraction on your pages? How many links can you eliminate?
- Improve Clarity with larger product images on your category pages
- How many options does your product have? Can it be reduced to one or two?
- Increase Clarity with high contrast text on white background
- Your customer buys emotionally and defends the purchase rationally. Get her excited.
- You don’t sell features. You sell solutions to problems. Value Proposition is relative.
- Have you tested embedding lead generation forms on the page vs. new page vs. popup form?
- Have you tested swapping right column with left? Worked for BabyAge.com
- Do you have large blocks of white copy on dark background? Try black text on white
- Can you move optional form fields to the Thank You page with additional benefit for filling them?
- Try replacing rotating offer banners with static images and value proposition copy
- Do your images have “action captions”? Include your CTA link
- Do your category pages include relevant & easy filters?
- Have you tested a two-column vs. three-column layout?
- Have you tested removing the navigation bar from landing pages?
- How strong is your CTA scent trail? Your key terms through the funnel should match.
- Do your landing page headlines match the words in your PPC ads?
- Select testimonials to support each product page’s main value proposition points.
- Does your home page offer visitors self-segmentation to increase funnel Relevance?
- Category pages offer huge opportunities. Try list vs grid view.
- Test category images vs. subcategory images on store pages
- Have you tested animation vs. static content. Worked for Hair Club
- Have you tested a Big Orange Button? We call him BOB. He works hard.
- Test a “factual” approach vs. an “emotive”. Worked for Sytropin
- Test Calls to Action; Order Now vs. Get a Quote vs. Instant Quote, etc.
Filed under: A/B Testing, Actionable Insights, Testing | Tags: Optimisation, Testing
Filed under: Analytics, Data, Datarati | Tags: Analytics, IBM, Optimisation
The emergence of new smarter systems which are interconnected and streaming real time information are presenting business and governments with a unique opportunity to transform decision making.
New opportunities to use this data to predict business outcomes, optimise old systems and spot trends before they happen are actually a reality.
Watch Video: http://www-03.ibm.com/press/us/en/presskit/27163.wss
Filed under: A/B Testing, Multivariate Testing, Research, Statistics | Tags: Consumer Behaviour, Free User Testing, Optimisation, Usertesting.com
Are you looking for some fast and cost effective user-testing so you can start implementing and actioning these insights?
Check out http://www.usertesting.com
Filed under: A/B Testing, Behavioural Targeting, Multivariate Testing, Optimisation, Segmentation, Web Analytics | Tags: Omniture, Optimisation, Test&Target
Optimisation is a fuzzy word. It’s been used to describe everything from decreasing page load time to improving user experience.
1) Testing - the process of testing alternatives on your site to see what converts best. Testing is most often implemented as simultaneously delivering alternative content to your visitors in a randomised fashion.
2) Targeting – the process of displaying relevant content to a particular segment or individual based on implicit and explicit variables such as gender, search terms, and intent. Targeting is most often implemented as delivering content to your visitors in a rules-based fashion. For some companies with enough site traffic, targeting can be delivered to the individual in an automated fashion.
Testing and Targeting: 1+1=3
Both efforts rely on the ability to deliver content dynamically on your site. Both are designed to increase key success metrics on your site. However, they are often separated as two completely different initiatives within a marketing organisation. While people seem to be interested in the idea of combining them, they are usually already siloed as different projects with different teams, budgets and timelines by the time we have the discussion.
Let’s first talk about testing by itself. It’s a great way to figure out what version your visitors prefer. If you’re just throwing new designs up on your site today on a wish and a prayer, testing is definitely a must. But then think about who your visitors are. Are they all people who are coming for the first time? Are they all visiting during work hours? Do they all enter on the same page looking for the same thing?
If your answer is no to any of these questions, then you have to ask yourself if it makes sense to assume that they all prefer the same winner in any given test. The easiest way to figure this out is to segment your reporting. That doesn’t change anything about how the test is designed or implemented, but it can give you additional learnings in the reporting and analysis.
What if you found out that the reason a particular version won was because it resonated deeply with your new visitors coming organically to your site? And balancing out that great lift was actually a negative result with other smaller segments such as direct mail and branded queries coming from paid search? This type of data is incredibly valuable for any organisation trying to get deeper insights into what their visitors are looking for and responding to. What makes it invaluable is to then take action on those learnings by delivering that targeted, winning experience to your organic, first-time visitors and then simultaneously beginning a new test on the rest of the traffic.
eHarmony ran a test with Omniture to understand whether adding tabbed navigation to a landing page would be more effective in getting users to convert. The hypothesis was that providing more information about the service directly on the landing page would be a positive change. Here are the different versions.
What they found was that the test actually performed worse for overall traffic, and that people preferred the simplified page without the AJAX navigation. Once they dug into their segments though, they found a more complex and interesting story. They had set up geo-segments to track how people from different countries behaved, and it turned out that visitors from Canada significantly preferred the navigation. This learning would never have been found without segmentation, and worse, the tabbed navigation would have probably been thrown out based on the overall negative lift.
What is Targeting Without Testing?
What is targeting without testing though? Isn’t it the same as just putting your hypothesis out onto the site and hoping your hunch aligns with your visitors? For example, let’s say you own a retail clothing site, and you want to target visitors who look at accessories and then return to the home page. You may wonder which accessories to now reinforce upon their return, but what if you should instead be asking yourself whether accessories is the right category to show? What if you should be featuring women’s clothing instead because there is a high correlation between the two or the potential for higher margin profit? Or what if showing 2 featured products instead of 6 would make all the difference? Do you know which price range you should be staying between? All of these questions are great opportunities to combine testing and targeting into a single initiative focused on creating conversion and revenue on your site.
BabyCenter ran a test with Omniture’s Test&Target module to understand the impact of increasing relevancy on one of their most highly-trafficked keywords: “baby names.” Below is the control version, along with the alternatives tested against it. What’s interesting to note here is that all of the alternatives have some element of targeting in them. Recipe B offers some relevant text, Recipe C adds some category links, Recipe D provides top 5 names of 2005 for both girls and boys, and Recipe E builds on Recipe B with a few more bullets of information. Can you guess which one won?
If you guessed Recipe D, then you are in sync with most of the marketers who see this case study. However, the answer is Recipe B, the alternative that provides the simplest reinforcement of just a headline and a couple lines of copy. Here’s the test data:
You can see that Recipe B provided 65.32% lift against control with very high statistical confidence. In fact, nearly every alternative performed better than the control except for Recipe D, the version that people most often pick as the winner. It makes sense that we naturally gravitate to Recipe D because it provides us with the most relevant information given that we are searching on the term, “baby names.” However, since we are measuring the success of the landing page based on those who sign up for the magazine, we have to balance driving both relevancy and engagement. Without testing this targeting effort though, we would have no idea whether we picked the right mix.
If you are in the process of testing today, I’d strongly advocate setting up segments so you can begin to see which ones behave differently. Targeting is a natural extension of testing, but don’t forget to go back and test your hunches as well, whether they apply to one segment or all of your traffic. Taking action on your data is the best way to do more with less, a strategy we will all have to follow more closely through the immediate future.
Content Referened from the Omniture Blog. http://blogs.omniture.com/
Filed under: Analytics, Data, Multivariate Testing, Optimisation, Web Analytics | Tags: Analytics, Data, Optimisation, Web Analysts
Do you have an internal web analyst at your company? Are they integrated with your agency? Didn’t think so.
Quite simply, unless web analysts are integrated with your agency’s data, analytics and optimisation team – they will add limited to no value to your company.
As industry guru, Avinash Kaushik puts it… “If there is a “killer app” for getting context to your web analytics data it is tribal knowledge. Information about initiatives, marketing programs, website updates, changes, management re-org’s :), server outages, ppc, direct marketing and on and on and on: Things that have a impact on your website.”
Web Analytics, and in turn Analysts, sit in a silo. This means that very often they have no idea about all the things that people are doing the site or to their acquisition strategies. So they look at all these numbers and metrics and trends and then like Tarot Card readers guess what the numbers mean!! A futile exercise.
There are lots of moving parts to a website and a lot of people involved in the holy exercise of creating something of value for your customers. It is a complex dance with many moving parts. . . .
The best way to get context is to seek out all the players and / or staying plugged into the various different processes to tease out vital context for your numbers.
“Ahhhh so you send out a big email blast five days ago!”
“You were running a multivariate test? Why did you not tell me in advance?”
“The shopping cart was down for nine hours! That explains so much, thank you. Kiss“
“We’ve adopted a new media mix model?”
“None of our last 6,000 campaigns were tagged! Pulling hair out!!!“
So on and so forth.
It’s time to step up to the plate and ensure your web analyst are working together with your agency to deliver you ultimate sales, revenue and profits!!
Filed under: Analytics, Data, Visualisation | Tags: Analytics, Data, Optimisation
Problem: How can we visualise the importance of data and actionable insights for each campaign? Something we can give our staff and clients to sell the true value of data, analytics and optimisation.
Solution: Jelly beans jar with a letter that reads:
“John sees hundreds of jelly beans in a jar. Will sees 142 blue, 127 white and 212 orange and that 20% of males 25 years and older dis-like the the taste of the black jelly beans, while 10% of women will eat all the red ones first and can then predict based on the data model, that their next likely choice of colour will be white”.
Call me to optimise your lollies: (02) 9016 1682