Post on 19-Oct-2014
description
transcript
Kherrin WadeDigital Media Account Director,Adido
@digiKherrin#letsdodigital
The A-Z of useful analytics
agenda
introduction to analytics
analytics alphabet concept
fundamentals
intermediate
advanced
questions
the analytics alphabet
the analytics alphabet…
…in numbers
75 man hours
14,654 words written
73 tips
63 pages
8 categories
3 levels
2 people #passion
the guide
fundamentals
intermediate
advanced
If you’re using analytics, you should at least be aware of all these features and tips
For regular users of analytics who want to get that little bit more into the detail
Key insights for the direct response marketer – taking conversion analysis that little bit further
setup
metrics / KPIs
goals / conversions
ecommerce
audience
traffic sources
content
insight
fundamentals
bounce rate
“The percentage of visitors who only visit one page during a session”
good or bad bounce rate?
All visits 60% bounce
rate
Direct visits25% bounce rate
Email visits80% bounce rate
good or bad bounce rate?
All visits 68% bounce
rate
Organic visits68% bounce rate
Twitter visits86% bounce rate
good or bad bounce rate?
All visits 95% bounce
rate
Time on page10:13
duration (avg. visit)
What is the purpose of your website?
Does performance vary by traffic source or visitor type?
positive or negative interpretation?
Time on site5 minutes
(High)
Avg. page views7 (High)
positive or negative interpretation?
Time on site3 minutes
(High)
Avg. page views2 (Low)
positive or negative interpretation?
Time on site30 seconds
(Low)
Avg. page views1 (Low)
direct
Direct will only be credited with the goal conversion (in GA standard
reports) if it is the only channel in a user’s journey to conversion.
direct
filters
Should always have two analytics profiles (Views) setup for any website
1) Completely un-touched (no filters)2) One with company IPs filtered out
Why bother?
Testing 100% data capture Prevent internal visits from skewing site performance and decision making
New visit(or)s
• If you have a website, like an industry blog, which has a high % of new visitors you have to review why it’s so high, because ideally you would want returning visitors to dominate.
• If you have an Ecommerce website with a low % of new visitors but you’re not generating enough sales revenue, you should assess you traffic sources and campaigns to see how you can drive more new visitors.
intermediate
experiments
Test different versions of landing pages (up to 5) to improve performance in a controlled environment.
In an experiment you can control:• the % of visitors who visit your test
page(s) vs. control page• objective of the test – goal /
ecommerce / site usage• test duration• traffic sources entered into the
experiment (controlled by the URL).
trends
Comparisons give you context:• look at the same data point over two time periods• look at 2 data points in parallel …to understand if the trends you are seeing are replicated across all metrics on your site.
Data segmentation can provide reasons:• identify which traffic source / campaign / keyword / device caused a
shift
y?
advanced
conversion (goal) paths
Useful views for interpretation include:
• Looking at how often different traffic source patterns emerge.
• Find out:• How many visits come from the same
source• Which traffic sources drive more first
visits or last
• Discovering what keywords tend to overlap with another traffic source or with other keywords (either before or after each other).
model comparison tool
Last interaction – any last action visit to the site (any source can be credited) – the default setting.
Last non-direct click - any last action visit to the site, except if the last action was a direct visit. This is useful if you believe direct visits wouldn’t have happened without other digital channel support.
Last Adwords click – when the last action was an Adwords click (useful to compare against last action to understand the % of last clicks which were via Adwords)
First Interaction – any first action visit to the site (any source can be credited). This is useful if you’re running awareness driving campaigns and want to attribute credit for this effort.
Linear – all actions in the user journey are given equal credit for the conversion. This is useful if you believe each touch point in a user journey is equally important.
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
who gets the credit?
1. Last interaction?
2. First interaction?
4. Linear?
3. Last Adwords click?
And, would you turn off any channel?
questions?
Kherrin WadeDigital Media Account Director,Adido
@digiKherrinkherrin.wade@adi.do
Thank you