Reading Atlanta Analytics

All of this business about paid tools vs free tools, and dare I say the whole concept of #measure, all boils down to the fact that today, we are a tool-centric industry, often to the detriment of being an expert-centric industry. — Stop giving web analytics tools the credit YOU deserve

Atlanta Analytics is a quite interesting blog – however, there aren’t so many posts. The author, Evan LaPointe, does have some nice visions and an interesting perspective, because he comes from a finance background.
I think he makes some important points, these are:

  • It isn’t about page views or uniques – it’s about money
  • Drive actions not data
  • Be a business person not a technologist
  • Demand your share – if you increase your company’s profit by $500,000 per year, you should demand a share of it

What is web analytics?

  • Quantify today’s success and uncover usability, design, architecture, copy, product, advertising, pricing and marketing optimization that will breed even more success tomorrow
  • Web analytics isn’t:
    • WA is not the measurement of something
    • WA is not defining success but translating it
    • WA is not Omniture, Google Analytics or Clicktracks
  • Web analytics answers the following questions:
    1. Who is coming to my web site?
    2. What are they trying to do?
    3. What is the gap between what they are doing and the ideal?
    4. What are some concrete ways we can close the gaps?
    5. How can we get more of these people?
  • These answers should be answered in context of growth and profitability
  • Analyst shouldn’t become married to one discipline otherwise they are losing the big picture
  • They are central and recommendations are driven by company impact and not by personal impact
  • Even if you cannot solve a problem by yourself, you have uncovered an important problem

Three enormous wastes of your web analytics time

  1. Analytics isn’t implemented in the dev process but afterwards
  2. You care about the correct unique visitors count
  3. You are trying to match two numbers from different tools: Trends not accounting

3.5 things that keep you from finding good web analytics people

  • 1: Good WA can be in your company
  • 2: A lot of experienced WAs are actually reporting writers
  • 3: Your interview process prevents you from hiring good people: if you fear change / that your flaws will be revealed and the application is able, then you probably won’t hire them
  • 3.5: Your salary is too low: increasing your conversion rate by 0.3% can mean hundreds of thousand of dollars additional revenue per month

Web analytics sucks, and it’s nobody’s fault

This is a handmade description for yet another propellerhead analyst who will sit around and run reports for people, get in arguments with other people (or those same people), “agree to disagree” with other departments, and will eventually call everyone else an idiot and will recede into their cave before ultimately quitting for a director-level position at a different, big, resume-enhancing company where the process will repeat itself.

It’s not their fault because a good position for a web analytics person does not exist in the companies that can use these people most. The bigger the company, the more important a small difference becomes. For a site with 10,000 visits a month, an analytics person would have to improve conversion by double-digit percentages to scarcely pay for themselves. For Wal Mart, moving the conversion needle a tenth of a percent probably pays their lifetime salary in a week

The effective web analytics person knows usability, they know some design, they know information architecture, they know HTML, they are good communicators and can thusly write good web copy, and ultimately they are businesspeople who realize the purpose behind all of these crafts is cash flow […] Rather than being careful, politically aware employees, effective analytics people are data-driven, quickdraw decision makers because they have two key assets:

1. Cold, hard facts in the form of data (and I don’t mean just Omniture data)
2. The ability to not have to decide: they can TEST

Big companies are ruled by coalitions of opinions, meetings, conference calls, and semi-educated executives. Data is actually a threat. Data is what gets people fired in big companies, not what gets them bonuses. Data is scary.

What are the REAL web analytics tools?

  • Question: How can you improve the long-term cash flow?
  • Where you need a decent degree of competency:
    • Usability
    • Information Architecture
    • SEO
    • Web marketing (PPC, display, email)
    • Social Media
    • Design
    • Copywriting
    • Website technology (HTML, CSS, SQL, JS, PHP/Ruby/Python/whatever)
    • Communication skills
  • Learn business goals -> department goals -> campaign goals -> personal goals

Have you lost faith in web analytics?

  • Make decisions as often as possible – aka fail faster
  • It isn’t about the newest technology – it’s about money
  • Don’t live in a vacuum – interact with different people and viewpoints

The purpose of web (or any) analytics

  • “We talk about being data-driven businesses. But these aren’t businesses built around a culture of measurement. They’re built around a culture of accountability.”
  • “The purpose of web analytics, or any analytics, is to give your organization the confidence needed to accelerate the pace of decisions.”
  • “We’re talking about being accountable to outcomes, not to some Tyrannosaurus on a power trip. That’s a big deal.”
  • “It’s about making big decisions often.” – Iterate, iterate, iterate

Reading Adobe’s Digital Marketing Blog (Part 2)

Avoid “anticipointment”: bridging the gap from ad to site

  • Ads and web site work together – don’t just invest a ton in one medium
  • Marketeers fall easy into the ad trap because it’s easier than creating an usable, engaging web site
  • People expect that the click from the ad will be of even more value than the ad
  • Online Marketing Value Chain: Basically Customer Lifetime Cycle
    1. Click ad, engage deeper in the landing page
    2. Make their way through conversion opportunity
    3. Become loyal customer
  • Most of these steps will be on the web site!

Creating a Successful Lead Nurturing Strategy, Part III: When Should I Call?

  1. Call within 5 minutes of the initial contact
  2. Call early at morning or late in the afternoon
  3. Call on Wednesday or Thursday – I personally tried this against Monday and Friday and it was highly effective
  4. Call them up to four times and send one email in the first 24h
  5. Test these tactics

Creating a Successful Lead Nurturing Strategy, Part IV: Your Long-Term Strategy

  • The main is not to sell but to maintain a relevant conversation
  • Offer relevant and personalized content – recent study showed that most content simply sucks, so watch out
    • Email – automated, personalized and relevant; reports, tips, guides, best practices
    • Phone – Follow up; provide deeper information, answer questions
    • Direct mail – reinforce what you’ve talked about; again personalized and relevant
  • This process should be repeated maybe once a month

Optimization Is Greater Than the Sum of Its Parts

  • Testing & Targeting are greater than just once
  • however often they are siloed
  • Start with testing and segment the results
  • This helps you to find better content for targeting

Building a Business Case for Optimization

  • Biggest problems are processes and politics
  • They hadn’t ownership over the site
    • Testing generates positive ROI!
    • Optimizing landing pages increases off-site ROAS (Return On Ad-Spending)
    • Test to fail faster – some of your assumptions are probably wrong
    • Dig into analytics, segment and provide insights

The Collaboration of Testing Ideas

  • Include other people and departments in your testing
  • Often people in development, IT, creative, etc. have ideas – just ask them
  • Test Ideas:
    • Test different landing pages: home page, product page, internal search, etc.
    • Reinforce ad text/graphics on the landing page/multipage setup
    • Test ads
    • Test incentives for submitting to your email database
    • Test emails
    • Build a story with the ad and following pages
    • Test different viral/referral elements: coupons, vouchers, …
    • Test different forms
    • Test % Off vs. $ off
    • Test your CTA copy, size, color, style
    • Test scarcity on offers
    • Test different copy approaches: informative, funny, benefits oriented, etc. and analyze segment behavior
    • Test signs of trust: security message, shipping info, return policy, etc.
    • Test geographical targeting
    • Test simple content vs. rich media
    • Test content vs. no content
    • Test free shipping vs. % off vs. $ off vs. guarantee vs. …
    • Test promotion tresholds: 10% on $50 vs. 15% on $100
    • Test different internal search results – hand picked, automated, editor picks, big brands, cheapest first, best selling first, highest rating first, etc. and segment(!)
  • Strategies
    • Understand your goal – what are you’re trying to improve?
    • Start with the bottom in your funnel – it’s easier to get more impact
    • Try to understand why alternatives work better
    • Try to improve one theme at a time, e.g. decrease registration drop off, copy style, etc.
    • Focus on big things: product shown, pricing, primary copy, images, offer, CTAs

Five Times to Test: 1 — When you need to optimize beyond the click

  • Data without analysis and communication is not very useful
  • Even then without taking action, it’s practically useless
  • Often lots of money is invested in driving traffic but less in converting the traffic
  • Example: large business $100MM PPC budget, less than $200k for optimizing landing page/website
  • Mark Typer, Wunderman: 15% Optimization, 85% Ad spending

Five Times to Test: 2 — To resolve internal disputes

  • Do you have a dispute? Just test the idea
  • Similar things can work different on different websites, e.g. CTA wording

Reading Kaushik (Part 7): Excellent Analytics Tips

Tip #3: Turbocharge Your SEM/PPC Analysis

  1. Measure your Bounce Rate
  2. Understand how vendors work
  3. Measure cannibalization rate vs. organic
  4. Experiment and Test
  5. Understand the multi goal of your site
  6. Measure the value of long tail keywords

Tip #4: Make Your Analysis/Reports “Connectable”

  • Make dry stuff more approachable
  • e.g. Flirters = Visitors with three pages or less
  • You can always include the definition if people are interested in it
  • You can link it up in a persona way

Tip #7: The Adorable Site Abandonment Rate Metric

  • Site Abandonment Rate = [1 – (total orders placed on the website) / (Total add to cart clicks)]
  • Checkout Abandonment Rate = [1 – (total number of people who complete checkout) / (total number of people who start checkout)]
  • Now you can segment, test and improve your rates

Tip #13: Measure Macro AND Micro Conversions

  • Macro Conversions: Buy something on your site
  • Micro Conversions: Write a review, sign up the email newsletter, etc.
  • Not all visitors want to buy something, therefore measuring micro conversions reveals more truth

Tip #15: Measure Latent Conversions & Visitor Behavior

  • Don’t just focus on immediate results — look a month later on the behavior of the acquired visitors
  • Especially for community-based websites (social networks, boards, etc.) later behavior is more important than just the sign up
  • Measure Loyality, Requency, Frequency

Tip #16: Brand Evangelists Index

  • Survey: Not at all satisfied, not satisfied, satisfied, very satisfied, extremely satisfied
  • Problem: Satisfaction rate is not very informative
  • Solution
    • Aim for delight
    • Penalize for negative rating
    • Index the results for communication
    • => Brand Evangelist Index (BEI): [[(Very Sat + Ext. Sat.) – (Not Sat. + Not At All Sat.)] / #Responses ] * 100

Tip #18: Make Love To Your Direct Traffic

  • Direct traffic is traffic that is driven by people who seek you actively out
  • Problem: Direct traffic can result from improperly tagged links / urls
  • Avoid:
    1. Missing WA tags on landing pages
    2. Untagged campaigns
    3. Improperly tagged campaigns
    4. Improperly coded redirects / vanity urls
    5. Non Async tag
    6. Links encoded in JS can be problematic
    7. https to http and vice versa don’t send referrers
    8. Multi and sub domains problems

Tip #19: Identify Website Goal [Economic] Values

  • What is the economic value of micro conversions?
    1. Assign campaign codes & track offsite converting goals
    2. Track online micro-conversions in offline systems
    3. Get the current “faith based” number from Finance
    4. Estimate relative goal values
    5. If everything else fails, just use $1

Reading Kaushik (Part 4): Tactical Analysis

Kick Butt With Internal Site Search Analytics

  1. Understand site search usage: What are they looking for?
  2. On which site do people search?
  3. How good are the search results?
  4. What do people search for after they search for one term?
  5. Measure outcomes

PPC / SEM Analytics: 5 Actionable Tips To Improve ROI

  1. Compare keyword performance for different search engines / PPC sites
  2. Focus on what’s changed, otherwise there’s just too much data
  3. Look at your impression share
  4. How is your ROI distributed – exceeds, meets or underwhelms expectations?
  5. How are the keywords matched?

Analysis Ninjas: Leverage Custom Reports For Better Insights!

  • Start with goals: Where is the company spending money? How is the bonus of your boss calculated? What is the worst thing on your company’s website?
  • Include outcomes
  • Reduce the number of reports
  • Match metrics up to reader – Personalize
  • Talk to people and understand what motives them

3 Advanced Web Analytics Visitor Segments: Non-Flirts, Social, Long Tail

  1. Non-Flirts, Potential Lovers: Page Depth bigger than 3 (depending on the distribution)
  2. Social Media, Baby: Tag your links and track by referrer
  3. Search Queries With Multiple Keywords [3, 4, 5, 10, 20]: Match keyword ->

Three Amazing Web Data Analyses Techniques For Analysis Ninjas

  • Calculate costs / profits for micro-conversions
  • Bring ratios / quotas into context: 0.01% conversion = 100 of 1,000,000 visitors convert
  • Not every visitor is convertible: only return and of return only valuable traffic (e.g. people visiting the pricing info)