Reading Kaushik (Part 6): Competitive Analysis

Competitive Intelligence Analysis: Metrics, Tips & Best Practices

  • What not to do?
    1. Comparing conversion rates is hard: different business strategies
    2. Pages / Content viewed is too individual and doesn’t really matter
  • What to do?
    1. Share of Visits by your industry
    2. Compare “up and downstream” against competition
    3. Share of Search traffic
    4. Share of brand and category key phrases
    5. Discover new search key phrases
    6. Traffic by media mix
    7. Psychographic analysis

The Definitive Guide To (8) Competitive Intelligence Data Sources!

  1. Toolbar data: e.g. Alexa
  2. Panel data: comScore, Nielsen
  3. ISP (Network) data: Hitwise, Compete
  4. Search Engine data: Google AdWords, Keyword Tool, Search-based Keyword Tool, Insights for Search, Microsoft adCenter Labs
  5. Benchmarks from WA vendors: Fireclick, Coremetrics and GA
  6. Self-reported data: Quantcast, Google AdPlanner
  7. Hybrid Data: Google Trends, Compete, DoubleClick AdPlanner
  8. External VOC data: iPerceptions, ACSI

Reading Kaushik (Part 1): Digital Marketing

I read Occam’s Razor for quite a while now and I really like Avinash’s style and insights. I thought it would be nice to reread most of his stuff and as a nice extra, I will post my notes on here.

I oriented each section by the section defined in his overview of all articles.

Enjoy!

The 10 / 90 Rule for Magnificent Web Analytics Success

  • There is lots of data but no insights
  • Rule: 10% in tools and 90% people/analysts
    • may seem over the top but
    • med-large websites are complex
    • reports aren’t meaningful by default
    • tools have to be understood
    • there is more than clickstream to analytics
  • If you don’t follow the 10 / 90 Rule
    • Get GA account
    • Track parallel to expensive solution
    • Find a metrics multiplier, so you can compare GA to old data
    • Cancel your contract and hire an smart analyst which will probably deliver more insights for less money

Trinity: A Mindset & Strategic Approach

  • The goal is to generate actionable insights
  • Components:
    • Behavior analysis: clickstream data analysis
    • Outcomes analysis: Revenue, conversion rates, Why does your website exist?
    • Experience: Customer satisfaction, testing, usability, voice of customer
  • Helps you understand what customer experience on your site, so that you can help influence their behavior

The Promise & Challenge of Behavior Targeting (& Two Prerequisites)

  • We have so much behavior data but you get the same content regardless whether you are here to buy or get support
  • There are BT systems but you have still think about the input
  • You have to first understand your customers good enough to create suitable content
  • Test content ideas first to learn what works and as evidence for HiPPOs

Six Rules For Creating A Data Driven Boss!

  • Paradox: The bigger the organization the less likely it is data driven in spite of spending lots of money on tools
  • It is possible to achieve this but you have to actually want to do and fight for it
  • 1. Get over yourself: Learn how to communicate with your boss and try to solve his problems
  • 2. Embrace incompleteness: Data is messy, web data is really messy but still better than completely faith based initiatives.
  • 3. Give 10% extra: Don’t just report data, look at it. Give him insights he didn’t asked for. Make recommendations and explain what’s broken.
  • 4. Become a marketer: Great analysts are customer people. Marketer as internal customer (like account plannner)
  • 5. Don’t business in the service of data: Data should provide insights not just more data. Ask: how many decision have been made based on data that have added value to the revenue?
  • 6. Adapt a Web Analytics 2.0 mindset:

Lack Management Support or Buy-in? Embarrass Them!

  • HiPPOs may be don’t listen to you but they better listen to customers & competitors
  • 1. Start testing
  • 2. Capture Voice of Customer: Surveys, Usability tests, etc.: Let the customer do the talk
  • 3. Benchmark against the competition, e.g. use Fireflick
  • 4. Use Competitive Intelligence
  • 5. Start with a small website
  • 6. Ask outsiders for help

How To Excite People About Web Analytics: Five Tips.

  • 1. Give them answers
  • 2. Talk in outcomes / measure impact
  • 3. Find people with low hanging fruit and make them a hero
  • 4. Use customers & competitors
  • 5. Make Web Analytics fun: Hold contests, hold internal conferences, hold office hours

Redefining Innovation: Incremental, w/ Side Effects & Transformational

  • 1. Incremental innovation, e.g. Kaizen
  • 2. Incremental innovation with side effect, e.g. iPod or Adsense
  • 3. Transformational innovation, e.g. invention of the wheel
  • Web analytics can’t probably create 3
  • Clickstream alone is also not enough for 1.
  • generally the more the better (Web analytics 2.0)

Six Tips For Improving High Bounce Rate / Low Conversion Web Pages

  • Purpose gap between customer intent and page
  • 1. Learn about traffic sources / keywords(!)
  • 2. Do you push your customers against their intent? Identify jobs of each page and focus on your call to actions.
  • 3. Ask your customer what they are looking for
  • 4. Get insights from site overlays
  • 5. Testing!
  • 6. Get first impressions from people, e.g. fivesecondtest

Online Marketing Still A Faith Based Initiative. Why? What’s The Fix?

  • Faith based initiatives like TV, magazines, etc.
  • Online marketing gives us useable data
  • and allows us to test easily
  • The web is quite old yet it is not in the blood of executives
  • Old mental: shout marketing, instead of new inbound marketing
  • Lousy standards for accountability
  • Let the customers speak
  • Benchmark against competition

Win With Web Metrics: Ensure A Clear Line Of Sight To Net Income!

  • Focus on the bottom line, i.e. profits
  • 1. Identify your Macro Conversion
  • 2. Report revenue
  • 3. Identify your Micro Conversions
  • 4. Compute the economic value
  • Net income = Unit Margins * Unit Volumes
    • Unit Margins = Price – Cost
    • Unit Volumes = Market Share * Market Size
  • Because Net Income is the goal, you have to measure Price, Cost, Market Share or Market Size
  • Which metrics help doing that? And if not, why do you track/report this metric?
  • They also depend on the strategies or more general goals of the organization
  • — let your “boss” decide what matters most to him/organization
  • identify clear metrics / KPIs for each used strategy
  • use the web analytics measurement framework as a reporting foundation (more to this later)
  • find actionable insights with segmented analysis

Digital Marketing and Measurement Model

  • Marketing with measuring helps you to identify success and failure
  • Digital Marketing & Measurment Model
    1. Set business objectives (should be DUMB)
      • Doable
      • Understandable
      • Manageable
      • Beneficial
    2. Identify goals for each objective
    3. Get KPIs for each goal
    4. Set targets for each KPI
    5. Identify segments of people / outcomes / behavior to understand why things succeeded or failed
  • What scope has the model to cover?
    1. Acquisition: How do people come on your site? Why? How should it be?
    2. Behavior: What should people do on your site? What are the actions they should take? How do you influence their behavior?
    3. Outcomes: What are the goals? (see previous summary)

11 Digital Marketing “Crimes Against Humanity”

  1. Not spending 15% of your marketing budget on new stuff
  2. Not having a fast, functional, mobile-friendly website
  3. Use of Flash
  4. Campaigns that lead to nowhere
  5. Not having a vibrant, engaging blog
  6. “Shouting” on Twitter / Facebook
  7. Buying links is your SEO strategy
  8. Not following the 10/90 rule
  9. Not using the Web Analytics Measurement Model (previous summary)
  10. Using lame metrics: Impressions, Page Views, etc.
  11. Not centering your digital existence on Economic Value