Sofia, October 2010

Experimental marketing:why and how

Andrey Sebrant,Director, Product marketing

A few facts about Yandex

Over 50 million users a month, around 15 million a day

Over 100 million search queries a day

Over 64% of search traffic in Russia

Over 2 600 employees in 7 offices across three countries

Over $300 million in revenues last year

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A very competitive environment

What do we rely on:

Dream team

Big math

Computing super power

Last but not least: a very efficient marketing

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“Digital” means a lot

Of course we operate in a digital media

We collect so many data that the entire marketing becomes digital in its core

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It takes many skills to be a pilot, much more than just ability to read devices.On the other hand, if you don’t know how to read them, the landing may be too hard.

Marketing is an experimental quantitative science

We study the world (people, products and markets)by creating models and testing them in experiments

Models are based on already known facts, observations, intuition and fantasy

Experiments or tests are carried out using standard scientific methods

Marketing studies happiness of users and customers. We have to predict what makes them happy even if they do not realize where the happiness is.

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Product is the king

On the Net this is true as nowhere else:

- everything is free- all competitors are a few clicks away

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Case study: Yandex bar

Hypothesis: short search window results in fewer searches because search queries are getting longer

Experiment: 50% of new bars have longer window. Tracking: search activity, search queries length

186%

104% 105% 103%100%

No. of searches Query

length, words

Query

length, chars

Churn Rate

Test bars/control bars

Yes, size matters, but not because of the query length…

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Case study: Churn rate

Loss of users may look scary

Don’t panic! Analyse this

It turns out that users are similar to isotopes; they decay like in nuclear physics

10000

60000

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1 2 3 4 5 6 7

Number of users registered during

week 1 and visiting the service at

least once during each next week

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100000

1000000

1 2 3 4 5 6 7

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y = 59125e-0.06x

y = 1E+06e-1.34x

1

10

100

1000

10000

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More about radioactive decay

The same percent of users quit service every week

Decay rate is characterized by half life, the time taken to decrease the initial amount of users by half

If the process is described by the sum of two exponents, there are two groups of users with different half lives

In many practical cases the churn

rate curve is the sum of two

exponential decay curves

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Translation from mathematics to marketing

Two groups mean not two isotopes in our case:we observe loyal (long half live) and casual users

Thus, we get quantitative metrics for loyalty which we can measure at the early stages of a new (or re-launched) service.

Why is this so important?

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Real-time obsession makes us blind to long-term effects

The internet is too fast

We all are obsessed with instantaneous measurements- «At the focus group they say…»- «usability tests show…»- CTR is dropping!…

And we often forget about life-long relationships with and love of our users ;)

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Source data: tables of registrations and visits

Every week you need a report on how many users registered in previous weeks are still using a service. Also, it’s a useful alerting tool.

Week Week 01, % Week 02, % Week 03, % Week 04, %

19.07.2010 -25.07.2010 100,00 45,93 35,86 32,58

12.07.2010 -18.07.2010 100,00 51,23 40,36 34,91

05.07.2010 -11.07.2010 100,00 61,93 49,25 44,54

28.06.2010 -04.07.2010 100,00 59,55 50,17 43,97

21.06.2010 -27.06.2010 100,00 61,13 48,75 43,46

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Churn rate is a good metric for evaluation interface changes

You can measure the effect of interface updates on users’ loyalty. Ideally, the new interface should be tested on a small percent of users.

Control group: new users registered in the old interface

Test group: new users registered in the new interface

Metrics to monitor: ratio of percent of loyal users, ratio of half lives

And then you can predict the future!

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0

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Churn rate and the budgets (usability vs. advertising)

Too much of the ad budgets are a waste

Loyal attracted = 5%,Half life = 3

Ad campaign Most advertising campaigns are too far from the ideal, because they mostly attract casual users and very few loyal ones

Loyal attracted = 100%,Half life is eternity

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No math, just common sense

Before pouring expensive usersinto the website,

plug the holes!

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But if you like math…

Site audience in a month n depends on the audience of the previous month:

NCAA nn )1()1()(

($)newnat FNN

)1;0(

($);

c

cmaх

G

GCC

New users come on their own

and thanks to promotion

activities:

Decrease in churn rate

costs money. But usually

it’s one-time expense:

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Enter the segmentation

Different groups of users

Different ads

Different sources of new users

Test and measure responses in each group,test and measure efficiency of every source and ad

And think it all over!

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This still is the most important tool for a marketeer

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Not only digital things matter

Thank you!Спасибо за внимание

Andrey Sebrante-mail: asebrant@yandex-team.rutwitter: @asebrantFB: www.facebook.com/asebrant