Introduction to Analytics

Objective of analytics is maximizing ROI aligned with various channels

What to measure?

Clicks > conversions > visits > Engagement

All the data is not gold!

To find what data you want.

MoM visits from affiliates : Affiliate-wise cost per acquisition

Top 10 search keywords: high conversion High cost keywords

Total Facebook Fans / Followers : Amplification Rate (Number of shares per FB post or RTs per Tweet on Tweeter)

Need to find the KPI to find the ROI

Identification of the right analytics tool depends on at what stage the business is. As tools  might be expensive and need an effort for implement.

Difference between using the wrong tool and using the tool wrong can give incorrect results.

80 – 20 rule by Avinash Kaushik – if you spend 20% on the tools, invest 80% on the person who uses them.

Accuracy of data : Web as a platform is not accounting level accurate.

ROI from offline media like TV, radio, print cannot be tracked accurately, waiting for the perfect data is wasting time.

Every report should tell a story: Grouping the keywords with conversion value – Brand Vs non-Brand can help in derive more insights.

Don’t kill the analyst with Reporting requests.

Classification, Analyze (make sense by break down): Splitting the data in more segments and making it understandable.

Segment can be done based on:

– Acquisition source (direct, search, display)

– Behaviour – Repeat, Purchasers

– Business Value – Cash cows, Freebie hunters

Ask the right question to the data and you will move closer to the answer / insight.

So What? can give you the real business question.

Target to be done on:

– Segments

–  One-to-one targeting

– automate the targeting

Experiment: Why should we experiment

To identify and achieve non-incremental improvements

Analytics sums up with the 4 stages:

Measure – Analyze – Target – Experiment

Analytics should be in house as a core function, if you are not sure, you can hire a consultant and start building the capabilities in house.