avinash kaushik

There are 10 posts tagged avinash kaushik (this is page 2 of 3).

Reading Kaushik (Part 5): Qualitative Analysis

Got Surveys? Recommendations from the Trenches

  • Work with an expert
  • Benchmark against industry: http://www.foreseeresults.com/, http://www.theacsi.org/, http://www.iperceptions.com/
  • Great insights are in the raw answers to your survey
  • Don’t show the survey too early
  • Think about your target segment that you want to survey
  • Treat them as a ongoing measurement system

Build A Great Web Experimentation & Testing Program

  1. Get over your own opinions
  2. State hypotheses
  3. Create goal and success metrics beforehand
  4. Don’t neglect side-effects of testing
  5. You can start small but get bigger
  6. Get people involved in testing: e.g. let them bid on outcomes
  7. Know the techniques and theories
  8. Evangelize people about testing

The Three Greatest Survey Questions Ever

  • What is the purpose of your visit to our website today?
  • Were you able to complete your task today?
  • If you were not able to complete your task today, why not?

Experiment or Die. Five Reasons And Awesome Testing Ideas

  • Reasons:
    1. It’s no expensive
    2. It’s quite fast
    3. It’s allows you to measure change
    4. You have the ability to take controlled risks
    5. It’s quite easy
  • Ideas:
    1. Fix the worst landing pages and be bold
    2. Test single page vs. multi page checkout
    3. Test number and placement of ads
    4. Test different pricing / selling tactics
    5. Test box layouts and other online stuff

Qualitative Web Analytics: Heuristic Evaluations Rock!

  • Trying to get tasks complete: e.g. place an order, look for support, etc.
  • You can try this in a group
  • Process:
    1. Write down task that you want to see completed
    2. Try to establish success benchmarks
    3. Walk through each task and note important findings
    4. Check with a best practices checklist
    5. Create a report: screenshots / screen recording
    6. Create a prioritized list with all the problems

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 -> 
    ^\s*[^\s]+(\s+[^\s]+){2}\s*$

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)

Reading Kaushik (Part 3): Strategic Analysis

Path Analysis: A Good Use of Time?

  • Customers like the path the want to, not the one you force
  • The tool don’t show which page in the path was most influential
  • Most tools don’t track the path correctly
  • Exception: Landing Page experience
  • Possible solution: Group relevant pages
  • Show most influential pages/li>
  • Make segmentation easier

Stop Obsessing About Conversion Rate

  • Overall conversion rate doesn’t allow for actionable insights
    • It only covers a small minority of all visitors
    • People are going to research on your site
    • People who want to learn about your company
    • People who need help with a product of yours
    • People that do something completely different
  • That is, you neglect a big part of your visitors
  • You’ll focus on short term gains
  • Better metric: Task Completion Rate
    • Helps you to cover all customers
    • Successes outside from conversions
    • Ultimately understand your customers better

Getting Started With Web Analytics: Step One – Glean Macro Insights.

  • Understand the macro level first
  • 1. How many visitors are coming to your site?
  • 2. Where re they coming from?
  • 3. What is the purpose of your website? What are your top three web strategies you currently working on?
  • 4. What are you visitors actually doing?

Consultants, Analysts: Present Impactful Analysis, Insightful Reports

  1. No data overload: Give value instead of data, provide recommendations
  2. Tie your data to business outcomes
  3. Use other data than just Clickstream
  4. Don’t make it boring
  5. Connect insights with actual data
  6. Meet the “exceptions of scale”: If you are a big agency or written a book on WA, then people expect more from you
  7. Do something unique

Paid Search Analytics: Measuring Value of “Upper Funnel” Keywords

  • Upper Funnel / Longtail Keywords can neglected because of the single session mindset
    1. Understand each stage of the customer purchase life cycle
    2. Map your keywords to each of those cycles
    3. Measure success for each cycle differently
    • Category Keyword: Bounce Rate
    • Category / Brand: Time on Site
    • Brand: Visitor Loyalty
    • Conversion/Product: Conversion Rate / Leads

Aggregation of Marginal Gains: Recession Busting Analytics!

  • Often web analysts don’t focus on the immediately achievable improvements
  • Simple things:
    1. Figure out where you are making money
    2. Check errors in your email campaigns
    3. Use funnels
    4. Fix your top landing pages
    5. Compare organic and paid keywords: Where are gaps between these two and why?
    6. Ask your customer
    7. Fix dumb stuff: e.g. check 25-point Website Usability Checklist

Analyze This: 5 Rules For Awesome Impromptu Web Analysis

  • Question: What would you change on this website?
  • Useful things to remember:
    1. Don’t start with your opinion: you are a proxy for customers / visitors => Better: State hypothesis
    2. Always offer alternatives
    3. Offer data, even when you don’t have access to the site’s data.
    4. State your assumptions about the site’s objectives
    5. Focus on obvious and non-obvious things: micro and macro conversions, competitor’s site, customer satisfaction, ideas for testing, demographic trends, etc.

Web Analytics Segmentation: Do Or Die, There Is No Try!

  • Pick at least some segments in: Acquisition, Behavior and Outcomes
  • #1: Acquisition: Where does the company spent its most money on?
  • How to segment:
    • Context: How many visits?
    • (Optional): How many were new?
    • Bounce Rate
    • What was the cost of acquisition?
    • What value could we extract at a per visit level?
    • How many were able to accomplish their goal?
    • Was what the total value added to our organization?
  • #2: Behavior
    • What are the visitors doing?
    • What do people want to do on your site?
    • How deep are they browsing on your site?
    • How long did they take time till conversion?
    • How often did they visited your site?
    • => Traffic source, conversion, average order value, actions, etc?
  • #3: Outcomes
    • Loot at macro and micro conversions!
    • i.e. video clicks, adding products to wish list, applying for a trial, downloading white papers, etc. etc. etc.

5 + 4 Actionable Tips To Kick Web Data Analysis Up A Notch, Or Two

  1. Go deeper — Don’t stop at the obvious border: compare off and online data, create CLV for ecommerce,
  2. Join the People against lonely metrics club
  3. Measure the complete site success
  4. Don’t just report one month: at least three months, understand your business’s cycles, create annotations
  5. Make insights in your data obvious: Better visualizations
  6. Segment your data (previous summaries)
  7. Don’t just look at the top 10 rows
  8. Step away from one-session thinking (later summary)
  9. Achieve multichannel analysis (previous summary)

Win Big With Web Analytics: Eliminate Data & Eschew Fake Proxies

  • Most reports are overloaded with data
  • Though, the readers want context and insights
    1. Eliminate all useless metrics and data in your reports
    2. Understand the desired outcomes

Rebel! Refuse Report Requests. Only Answer Business Questions, FTW.

  • Context is important – no business is the same
  • Answer business questions – what’s the driving request for the data?
  • Attributes of a business question:
    • They are usually open-ended and on a higher level
    • They need likely more information than just visits, bounce rate, etc.
    • They are seldom answered with tables

The Difference Between Web Reporting And Web Analysis

  • Data puking isn’t web analysis
  • Signs that you are doing web analysis:
    1. Actions instead of data
    2. Work with the business, measure economic value
    3. Use the web analytics measurement model (previous summary)
    4. You are doing a bit advanced statistics
    5. If you work with targets
    6. You provide context
    7. You segment your data effectively
    8. If you can provide an impact for a recommendation
    9. If you use less than four metrics in a table
    10. If you use multiple data sources

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