don't just gamble: data driven strategy for the launch of 2 new global analytics products

Don’t Just Gamble

Marco De Cesaris http://www.marcodecesaris.com/about

Data

Driven

Strategy

Launching 2 New Global Analytics Products

Data Driven Product Strategy

Product 1 (P1 PRO): price strategy for a new analytics product

Product 2 (P2): implementing a product analytics infrastructure for a new product

Marco De Cesaris http://www.marcodecesaris.com/about

Introduction

•  This is a real advisory document that I conceived and produced upon request of a global company.

•  I have never received any compensations in any forms for this work.

•  In order to make this document publicly available and for respect of the company in object, I got written approval from the company in order to publish this work and I removed any identifiable information for the company in object.

•  I replaced the name of the company with a generic name “Client”. •  I also replaced the name of the 2 products respectively with

“Product 1 PRO” (or “P1 PRO”), and “Product 2” (or “P2”). •  Then replaced the name of the different publishing platforms with

the generic “Platform #”.

•  For any information, details, questions, suggestions feel free to contact me directly through my LinkedIn account: http://cn.linkedin.com/in/marcodecesaris/ .

3 http://www.marcodecesaris.com/about Marco De Cesaris

Product 1 PRO (P1 PRO)

Price strategy for a new analytics product


Summary

1.  Product description 2.  Web survey methodology

–  Additional Questions

3.  Data analysis 4.  Pricing, insights and recommendations


http://www.marcodecesaris.com/about 6

Product Description

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Product Description

•  Target audience: smaller publishers

•  Features: end-user demographic, integration with customer’s product tracking and crash systems, social media listening, sentiment analysis, etc…

•  Price assumption: 15 USD per month

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Web Survey Methodology

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Web Survey Methodology

•  Running period: 1 day

•  Explicitly collected data: –  Publishing platform, interest in this

product, favorite platforms for this product, five different prices, demo, turnover.

•  Sample size: 203 users (called customers from now on)


Survey: Strengths & Weaknesses

•  Strengths: –  Cheap/Free; Fast; Onsite (directly

managed and data owned); Possibility of data matching with existing data and customers behavior; Data integration using existing data for registered customers

•  Weaknesses: –  Only ran for 1 day; Some key questions

missing (e.g. weighting the different features); see questions list in the backup section.


Robustness And Future Research

•  See questions list in the backup. –  E.g.: Analyzing web traffic and choosing

the right period in order to avoid anomalies and biases; Newbies VS. Long term customers; Level of engagement with current product(s); Survey language; Etc…



Data Analysis

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Data Analysis

•  Data cleansing •  Overview and Insights


Data Cleansing


Data Cleansing 1/2

•  Main focus of this analysis is pricing. •  Several price fields were completely

blanks. •  There is a logical order in the price

questions: e.g. defining a “cheap” price = 5 USD, it conflicts with the same user defining a “too expensive” price = 5 USD.

How was it sorted out?


Data Cleaning 2/2

1.  Removed 48 records where all the 5 price questions were blank; 2.  Removed 19 records where:

“too expensive != blank” <= “worth it” “too expensive != blank” <= “cheap” “too expensive != blank” <= “bargain”

3.  Removed 6 records where: “bargain != blank” < “cheap”

4.  Removed 1 record where: “worth it != blank” < “bargain”

5.  Removed 3 outliers (less than 2,5% of total left records, only upper end). Logic: as soon as the “vertical” price double from previous ordered value. Found 2 outliers in “cheap” and 1 outlier in “too expensive”.

ORIGINAL SAMPLE: 203 users FINAL CLEANSED SAMPLE: 126 users


Overview And Insights


62% customers1 between 26-45


0%

5%

10%

15%

20%

25%

30%

35%

40%

Under 25 26 to 35 36 to 45 46 to 55 56 to 65 Over 65

Age Distribution

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1. Surveyed customers

Gender balance


51% 45%

4%

Gender Distribution

F

M

(blank)

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$10K-20K is the dominant segment*


0%

5%

10%

15%

20%

25%

30%

Turnover Distribution

*Bear in mind that the last category is the upper end and it includes everything above $300K

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Cross Platform Publishing


Platform 1 98%

Platform 2 94%

Platform 3 68%

Platform 4 32%

68% of customers publish on 3 platforms: the biggest being Plat 1 and Plat 2, followed by Plat 3.

Q1. Is the platform development’s cost strongly related to the number of platforms launched? Q2. Do we have any strong correlation between maintenance/launch cost and number of platforms?

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Product Differentiation Opportunity?*

•  Priority should be given to Plat 2, followed by Plat 1 and then Plat 3. P1 PRO on Plat 4 is not requested.

•  Plat 2 seems to be the most popular platform for these new features.

•  Maybe there is a feel of lack of analytics on Plat 2 (vs. Plat 1)?

•  Are publishers seeking ways of better monetize Plat 2?


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

On which platform customers want P1

PRO?

*Additional questions in the next survey/research (weighting single features).

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Pla

tfo

rm 3

Pla

tfo

rm 2

Pla

tfo

rm 1

P1 PRO “Users” Publish On All Platfs

•  Across customers who are willing to have P1 PRO, almost all of them are already publishing on Plat 1 and Plat 2.

•  Plat 3 follows, where 70% of customers who want P1 PRO are publishing.

•  Across customers who want P1 PRO, only 33% publish on Plat 4. The number of customers who want P1 PRO on Plat 4 is irrelevant.


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

TOT

Where P1 PRO potential customers

are publishing

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Pla

tfo

rm 1

Pla

tfo

rm 2

Pla

tfo

rm 3

Pla

t 4


Pricing, Insights & Recommendations

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Price, Insights & Recommendations

•  In order to identify the most suitable price we need to understand whether the objective is penetration or revenue optimization.

•  Contingency table was built between “worth it” and “acceptable” price1.

•  An eye has been kept on the “other” prices’ categories, to make sure there was no conflict with the final recommendation.


1. Logical assumption (according to the questions in the survey) is that if a user accept price X, but also states that the product is still worth it price Y>X, then will subscribe even for price Y. The other prices’ categories have been used as a limit references.

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15$ Not Necessarily The Best Choice

Worth it Price

Acc

ep

tab

le P

rice

Count


•  Most customers who “accept” a price of 15 USD actually consider the product “worth it” 25 USD.

•  Across customers who consider the product “worth it” 25 USD (and would still buy it) there are also several customers who declared to “accept” a price lower than 25 USD.

NEED TO OPTIMIZE THE PRICE

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Pricing Strategy

Price (USD)

# customers subscribing

Monthly Rev

(USD)

% penetration Objective Option

12 Option

22

15 100 1500 93% Penetration - -

20 92 1840 86% Hybrid - 2000

25 78 1950 73% Revenue 2300 2500

30 62 1860 58% - -

35 47 1645 44% - -

40 45 1800 42% - -

Option 1: Unless priority is penetration, we could set an initial price of 20 USD per month, reaching 86% of customers interested in P1 PRO1, and make this as a promotional offer for the first three months, then eventually apply the official price of 25 USD (this price is mathematically accepted by 73% of customers who want P1 PRO).


Option 2: Promotional price of 15 USD (focus on penetration) and persuade initial subscribers for the official price of 20/25 USD from the third month going on. Option 3: 25 USD, and invest part of this revenue3 in marketing activities. 1.  Assumption is that the removed records won’t be interested in subscribing to P1 PRO. This will keep conservative revenue

projection. We could further investigate the removed records (and ask additional questions) in order to understand whether they could be part of the subscribers base.

2.  From the third month on. 3.  (25$-15$)*(73%)*(# interested customer base). As long as 15 USD is a price that makes Client happy and on balance, we can

use this calculated budget as a “free” budget for marketing activities to increase brand/product perceived value

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Pricing Considerations

Option 1 and 2 in the previous slide (promotional price for the first 3 months) could potentially persuade the early skeptical customers to keep the subscription for a higher price that they wouldn’t accept at the initial stage, but maybe are willing to accept after trying the product.


20-30 USD Per Month Is The Price

Cheap (USD) Bargain (USD) Worth it (USD) Too Exp (USD) Acc (USD)

Mean 11.93 23.07 37.02 56.95 26.14

Median 10.00 20.00 30.00 50.00 20.00

Mode 5.00 10.00 50.00 50.00 20.00


A price of 15 USD could be perceived as a cheap price (too close to Mean and Median for Cheap). A too expensive price would start from 50 USD. Considering the values of Median and Mean for Bargain, Worth it and Acceptable price, a recommended price would fall in between those values. A price between 20 to 30 USD is the right choice (unless penetration is a priority for Client). To be noted in the category “worth it” the “mode” value is higher than both Median and Mean.

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P1 PRO Revenue Projections

S = # smaller publishers 62% S1 = base of customers seriously interested in P1 PRO

Monthly Revenue for P1 PRO =

Monthly price2 * % penetration2 * 62% S


1.  62% = 126/203, where 126 are the records after cleansed initial sample. The conservative assumption here is the 203-126 records are not interested in P1 PRO.

2.  Monthly price and % penetration from the table on slide 27.

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Additional Considerations


Focus: 26-35 And 36-45 Years Old

62% of the customers surveyed is between 26-45 years old.

55% of men 26-35 would consider worth it a price higher then 40 USD per month, while only 20% of women in the same age range would agree on it.

71% of women 36-45 would consider worth it a price higher than 40 USD per month, while only 50% of the men in the same age range would agree on it.


Gender

Age

Pri

ce W

ort

h it

Younger Men and

Older Women would pay

more

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10-20$: Heterogeneous Turnover

Customers with turnover 10-20K USD1 are happy to pay either 10, 30, 50 USD per month. Worth it investigate further. Could lead to a product differentiation (P1 PRO and P1 ENTERPRISE). It could be that the different segments prefer completely different features, hence 2 products with different features could be developed in order to also maximize the revenue for Client and the needs of our customers. Customers with turnover more than 300K USD are heterogeneous as well (but slightly more inclined to higher price): happy to pay 20 or even 50 USD per month.


Turnover

Pri

ce W

ort

h it

Opportunity for Product

Differentiation: P1 PRO VS. P1 ENTERPRISE

1. Segment 10-20K USD turnover is worth it further investigation, even because it represents 24% of customers who declared their turnover. It is the largest segment.

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Q&A

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Product 2 (P2)

Implementing a product analytics infrastructure for a new product.

Tracking, Key Performance Areas & Metrics

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Summary

1.  Product description –  What is in it for Client –  Connecting Ad Networks to Customer’s

Account on Client’s Platform

2.  Tracking solution –  Key Performance Areas & Metrics –  Tracking Systems –  Other processes/reports/interfaces –  Business decisions supported

3.  Some thoughts



Product Description

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Product Description

Product 2 (P2) allows users to link their P1 Account with their Ad Network Accounts. Once this is done users are able to dig into their: •  Advertising Revenue •  Advertising Expense Full picture of customer’s product Revenue is provided (One off Sales + Recurrent Sales + Advertising).


What Is In It For Client?


What Is In It For Client?

•  New generation of Market Intelligence Product.

•  Additional Revenue/Customers for Client by providing insights on Ad Revenue/Ad Expense related to customers’ products (Intelligence Product).

•  Possibility of combining these data with data from other sources (e.g. Turnover/Ad Revenue; Launch time/Ad Revenue; Ad Expense/Product Ranking; etc…)


Connecting Ad Networks To Customer’s Account on Client’s Platform


Connecting Ad Networks


Login Page Logged In Account Management

Ad Network Selection

Ad Networks Credentials

Backend Checking

Error Page

Error Email

Successful Page.

Data Collection Started

Successful Email

Ad Networks Campaigns List

Campaigns Linking

Ready To Use Product 2

Back-end system / Database

Web Page / Web Analytics Tool

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Tracking Solution

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Tracking Solutions

•  Key Performance Areas & Metrics •  Tracking Systems •  Other processes/reports/interfaces •  Business decisions supported


Key Performance Areas & Metrics



Measuring P2 Success (Client’s Perspective) Key Performance

Area Metric

Acquisition Awareness: # mentions/pr/articles/searches over a time period New visitors over a period

Activation

Cost Per Activation Net P2 Adds: New P2 Users – P2 Cancelled

P2 Activation: Funnel completion: # completed / # started

P2 Activation: # attempts to success per user

P2 Activation: # error mails / # total mail AND # unique clicks on error link mail/referred successful completions

New Users Activation: # new users referred by P2 / # total new users

# new users acquired / # total visitors over specific time period

P2 Activation: # P2 completion / # Total P1 active users

Retention Engagement: % P2 active users

Engagement: % P1 active users / % P2 active users

Revenue

# P2 Intelligence Customers / # Total Intelligence Customers

P2 # free users who Upgraded to Intelligence Customer / # P2 Users over a time period

# ad networks linked per user / # total ad networks available over spec time period

P2 Intelligence Rev / Total Intelligence Rev

# Intelligence Products Sold per customer over time period

Revenue per customer over a time period

Referrals # Shares over a time period

Users Satisfaction & Product Improvement

Surveys: users suggestions, features needed, dislikes, etc.


In Case Of Paid Media

•  On top of CPA, also Paid Media performance by channel would need to be taken into account.

•  Some example of metrics: –  CPA by Channel –  % P2 Active Users by Channel




Measuring P2 Success (Customer’s Perspective)

Key Performance Area Metric

Activation P2 Activation: # attempts to success per user

Retention

Engagement: % P2 active users

Engagement: # ad networks linked per user / # total ad networks available over spec time period

Engagement: Time spent per user on P2 section / Time spent per user on P1 section

Referrals # Shares over a time period

Users Satisfaction & Product Improvement Surveys: users suggestions, features needed, dislikes, etc.

Marco De Cesaris

Tracking Systems


Tracking Systems

1.  Web Analytics Tool –  As most of the metrics in the previous slides are based

on web pages tracking

2.  Internal Database / CRM system –  Mainly for PII, for storage of API Keys, Passwords,

Customers Spend for Client’s Products, Account Creation Date, User Declared Information, etc…

3.  Business Intelligence Tool –  Later on, in order to aggregate all the data from

different sources with the objective of achieving a SCV. Initially this is not needed as most of the tracking/measurement can be monitored through simple Web Analytics UI + Data from Database/CRM (through SQL queries or CRM UI).


Other Processes, Reports, Interfaces


Processes, Reports, Interfaces

•  Usual daily/weekly/monthly reports

•  One Special Metric: # New Users by P2 / # Existing P1 Users Upgrades to P2

•  Display Real Time Performance Across The World –  Display the OMTM on monitors within the different

offices around the world so that everybody within the company knows in real time how P2 is performing in real time and can feel his/her contribution to the achievement (or alternatively feel the immediate need of actions to be taken in order to improve the performance)


P2 Performance Display


P2 New Users

Yesterday Today

120 198

Business Decisions Supported


Few Examples 1/3

•  If “unsuccessful” customers are not completing the P2 linking through the error email, then optimize through on site / off site retargeting.

•  Is there any drop off point in the P2 funnel? Then optimize accordingly.

•  If P2 is not perceived valuable to intelligence customers then highlight the benefits through targeting/pr.


Few Examples 2/3

•  Is P2 producing additional revenue?

•  Is P2 producing additional new intelligence customers?

•  Spend more money on New Users Acquisition through P2 promo or Optimizing Existing P1 customers base?


Few Examples 3/3

•  Which one is the most efficient customer activation channel?

•  If P2 customers are not upgrading to intelligence customers, tease them through case studies or targeted campaigns (on/off site)

•  If P2 customers have a common profile, then target similar customers/users who are not P2 customers yet



Some Thoughts

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3

Some Thoughts 1/2

•  Ad Networks is just part of the Advertising. How about if a customer’s product allows an Advertiser to buy Ad Inventory directly from a Publisher (without any needs to go through an Ad Network)?

•  The tracking system mentioned in the previous slides would be beneficial for all the different business units/departments: –  Front-end UI/UX -> Test Different Layouts; A/B testing; Path Analysis; –  Back-end -> understanding where customers are having problems in connecting/linking the

ad networks; suggestion on identify a better way (automatic way) of linking Ad Network “Campaigns” with customer’s account on Client’s platform; Double check trends of web analytics with internal database data

–  Customer Segmentation: Profiling P2 customers and target similar profiles; Channel conversion; Existing P1 customers VS. New customers; etc…

•  Customers must spend time manually linking campaigns to individual products: how about we create a smart system that can read and take a “guess” to the most reliable matches between products and “Campaigns”? (to be confirmed with just a click by the customer). We could do that through textual analysis (assuming the “campaigns” are identified through a string of characters leading to meaningful words). Another option could be given by providing recommendations on how to name the different “campaigns” (name and convention) so that whenever new “campaigns” are imported in P2 those are automatically linked to the different products. E.g. campaign-name: id-productname-period-device-size (this would also provide additional data to both customers and Client’s Intelligence Products). Think for example by writing a report about Ad Revenue by Ad Size, on which devices and during which period ( just to mention few extra bit of information).


Some Thoughts 2/2

•  Relation between products and Ad Networks can be: –  1 to many –  Many to 1 –  1 to 1 –  Many to many

•  On top of it we have 2 ways of linking Ad Networks: Ad Networks as Ad Serving Platforms within the products (producing Revenue for our customers), and Ad Networks as Ad buying Platforms for promoting the products (producing Cost/Ad Expense for our customers). Those can be completely different Ad Networks.

•  Additionally Ad Networks include Mobile, Web, Outdoor, TV, and other kinds of Medium. •  P2 customers eventually would definitely be interested in the Ad Profit (maybe even by

Device or by kind of Ad Network – e.g. Mobile Ad Network, Web Ad Network). •  Will P2 also be available in Client’s App? It could happen that Tablet customers adopt P2

at a higher rate than the Web customers. We should definitely keep an eye on it. Assumption is that customers on tablet are always logged in, while customers on web are not.

•  Connecting Ad Networks: The third bullet point states: “Click on the name of an ad network….”. I think would be great and better if we can provide a “SELECT” all the ad networks one off through a tick box and wherever the tick box is ticked we expand the form fields to allow typing in the credential for each ad network ( just on a single web page).



Q&A

Marco De Cesaris


Backup

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P1 PRO Questions List 1/2

•  Was the survey free? •  How do you define “smaller” publishers? Is this related to the turnover? Then there is a

risk that you included in the survey also bigger publishers (not sure if you wanted it or not). Is more than $300K turnover considered as a big publisher? Do you want to sell P1 PRO also to big publishers?

•  Survey ran only one day. •  Which day? •  Why that day? •  Any campaigns/PRs activities around that period? •  Any anomalies in the traffic for that day? •  Why not analyzing periodic web traffic and run survey accordingly? •  How was the survey taken? Popup? Click on a link? Visibility? Randomly? How did you

build the sample? Specific targeted audience? What was the success completion rate? •  How often customers of P1 use the service? How many times per day? Per week? Per

month? •  What is the different engagement? •  Any trends showing that newbies engage less than long term customers? This could

massively affect price strategy and hugely increase selling price for this service and also revenue.

•  Country/Language could affect how users understand the questions. Language used in the survey?


P1 PRO Questions List 2/2

•  Was there any incentives/promotions to take the survey? Why would a customer take the survey?

•  Many records where blanks (price columns). Was there any questions to double check the intentions/interests of these customers? Would the survey stop or proceed accordingly in case customers were not interested in the product? Potentially a further investigation would help in understanding whether these customers don’t mind about price or they are not interested about P1 PRO, or any other cases. This would definitely help also with more accurate revenue projections.

•  Any correlations between price-customer engagement? Price-account opening date? •  Customers of P1 maybe are not buyer decision makers or influencers; if there was a

present price for P1 it could happen that those customers/users don’t even know that price.

•  Some of the information about customers could be double checked against their activity on P1 (e.g. where they publish), rather than just being asked within the survey.

•  Were there any segmentations in the surveys between giants customers and indies customers (on top of the information about turnover?).

•  Questions to be included in the survey (or as a next step) would be to weight the different features offered within P1 PRO. It could happen that specific segments prefer just specific features and are happy to pay a higher price => We could develop 2 different products for different prices and different audience/needs: “P1 PRO” and “P1 ENTERPRISE”.

•  Right sample calculation: http://www.surveysystem.com/sscalc.htm


EXPERTISE:

Marketing Technologies, Custom Data Solutions, Advertising, Data Strategy & Planning, Advanced Targeting, Marketing, Smart Advertising,

Innovation, CRM, DSPs, DMPs, Data Enrichment,

Measurement, Online & Social Media,

Insights and Analytics, Optimization.

COMPANIES/CLIENTS I worked for:

About Me


http://www.linkedin.com/in/marcodecesaris

Get In Touch


Credits

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don't just gamble: data driven strategy for the launch of 2 new global analytics products

Data & Analytics