Monday, 14 November 2016

Customer Lifetime Value- CLV or LTV -Basics

What is an LTV, why is it important?

What is LTV?
Customer Lifetime value can be defined as the projected revenue that a customer will generate during their entire lifetime. It is very important for the company to understand this metric as it helps them to shift their small term focus like quarterly profits to long term focus like customer relationships.
Why it is important?
It is a critical metric that tells a company how much Total Net Profit a company can make from any give customer. Apart from this, it also helps companies to-
1.Tell how much you need to spend to acquire new customers/retain old customers
2.How much repeat business company can expect from certain customers
3.How can a company offered products and services customized for their best customers
4.How much should a company spend to service and retain a customer
5.What type of customers you should focus to acquire
6.Align marketing campaigns along with the budgets, finances etc
7.Effective customer segmentation- based on their LTV
8.Customize marketing strategies for future audiences
      9.Allocating and managing budgets efficiently, select right media, channels, platforms etc 

LTV Formulas- How do you actually calculate LTV





























3 Major Formulas to calculate LTV- Final result is Average of 3 formulas.
Generally all the 3 methods are used and finally an average is taken to get the LTV.
All 3 formulas gives absolutely different figures

Please note that there are many formulas to calculate LTV and none of them is universally accepted

Example 1 -How to calculate LTV?









































Data available (sample- for ref.)
Avg. customer lifespan (t) =4 years  > (Formula is 1/Churn rate)
Customer retention rate (r) - 75% {so the churn rate will be 25%}
Profit Margin (p) – 20%
Discount rate (i) - 10%
Number of weeks per year= 52
Avg. Gross margin per customer lifespan (m)= $14204.32*20% = 2840.86    (20% of the simple LTV output)
Calculations (we will calculate by all 3 methods and then take average)
Simple LTV = 52(a)*t = 52(68.29)*4
                   = $14,204.32
Custom LTV= t(52*s*c*p)
                    = 4(52*9.6*3.94*0.2) = $1573.48
Traditional LTV= m{r/(1+i)-r}
                          =  2840.86{.75/(1 +0.1)-0.75}
                          = $ 6087.56
Average LTV= ($14,204.32 + $1573.48 + $ 6087.56)/3
                     = $7288.44


Example 2 -on how to calculate LTV






















Average order value/Revenue:  $20       Frequency (of purchase)- 12 times
Average customer lifetime period- 5 (from the assumptions-in years)
 Profit margin- 70% (from  assumptions on the left)
Retention rate- 80% (from assumptions on the left)
Discount rate - 15% (industry standard for start-ups who have scaled up, got funding and are profitable- as per discount cash flows . Details here)

Formula for CLV = (Revenue x Frequency x Lifetime x profit margin x retention rate)/(1 + discount rate – retention rate)

CLV= (20*12*5*0.7*0.8)/(1+ 0.2-0.8) = $1680

Mobile Attribution guide - Part 6 - Review of attribution
















Overall App Journey

The overall app marketing process can be split into 5 major areas.
1.New user acquisitions- Attract new users + Download the app
2.Installation- This is the stage where user opens it for the first time
3.Engagement- User opens the app, engage with it. Can be organic (self driven) or promoted (ads)
4.Remarketing- Attract existing users, engage and drive more traction

5.Re-engagement- Completion of an event in the app- deep links usage


Attribution benefits


1.Accurately measure mobile campaign performance
2.Accurately measure revenue and ROI
3.Improve personalization efforts as you get the holistic view of the customer journey and touchpoints
4.Make powerful optimizations
5.Compare multiple networks and see which is performing and which one does not
6.Manage budget efficiently and reduce media wastage
7.Correctly attribute credit to the source and manage payouts without efforts

Mobile Attribution guide - Part 5 - Things to consider before you start

Point out some findings of your previous work.


1.       You cannot run the campaign on Mobile web if you want deterministic approach and looking for device ids. It is only available for in-app inventory and also the ad network should agree to provide it. Not every Ad networks agree or have the capability to provide it
2.       Before selecting the attribution partner, make sure that they support both- mobile web and mobile app
3.       Also check that the attribution partners can pass unique variables(like order id etc.) through conversion tag so you can validate the purchase
4.       Be very careful while selecting the parameters like de-duplication and reattribution window. This should be in-line with the overall app journey and time taken for overall conversion
5.       Very short reattribution window is not advisable, it should ideally be 7 days
6.       Be careful while you look at the attribution for Facebook (28 days) and Google (30 days), they might not be in-line with your attribution default window. Facebook even charges for impressions based conversions that happens within 24 hours
7.       Multiple vendors generally  claim for the same app events or install events if the parameters are not set properly
8.       Share the revenue tokens and purchase tokens details with all the vendors so that they have the clarity on the revenue that they are generating. It’s one unique token for each and created one time. This will give your vendors the total purchase and total revenue generated and helps them in optimizing the campaign
9.       Always have the postback passed back to the networks, this will help in optimization. For affiliates, always get publisher id, ask them to append URL
10.   Use S2S and callbacks to fetch any data into the CRM and Business Intelligence systems
11.   Make sure that all the vendors work on same attribution window. If one network has a look back period of 24 hours and another has a lookback period of 7 days, it’s likely that the latter network is taking credit for more installs
12.   Leadership should also be involved and should share the same vision, if not it will not be successful
13.   Frauds clicks from devices, channels and platforms causes serious issues in the overall attribution
14.   Work with a vendor who offers  purchase verification, fraud prevention, feature like cohort analysis, customizable attribution modeling, uninstall analysis, deeplinking, re-targeting, re-engagement, audience segmentation, de-duplication, tracking purchase in different currency  etc. to name a few
15.   You don’t have to create separate trackers for each country when you work with any ad networks. Country data can be obtained by just searching the country name. Just have a single unique tracker for each network/partner 
16.   Keep the view through attribution to  zero or in case if you still want to track it, it should not be beyond 24 hours


17.   Make use of all the segments and track each network upto 4 levels-Network, campaign, Ad-group and creative (I used Adjust before)

Mobile Attribution guide - Part 4 - Common Issues

What are common issues?


1.       For mobile attribution- no model or technique is universally accepted yet (unlike the traditional web attribution which is perfect)
2.       Not all models can measure everything single handedly like Platform (iOS/Android etc.), Engagement type(Click vs view), Conversion type(Install vs events) and Flow(app to app vs web to app)
3.       None of the model is 100% accurate
4.       Every Mobile attribution partner has multiple methods of attribution so selection of vendors becomes very difficult- they use either deterministic or   probabilistic identifiers- so by using any one, so it  not possible to get the clear picture. Even if both are used still its not 100% accurate
5.       There are multiple devices that people use to engage with brands, and without a universal method to track campaigns across all of these devices, the efficacy of mobile campaigns can be underreported or devalued.
6.       Users move from online to offline, so getting the credit for mobile in discovery phase becomes very difficult
7.       Cross device attribution model is still not universally developed and accepted
8.       Industry lacks a scalable device agnostic model that can tell how the upper funnel mobile touch points attributed to the lower funnel sales and revenues
9.       A typical user journey is becoming far complex and fragmented
10.   Cross device and cross channel campaigns possess a serious challenge for attribution
11.   The attribution is still based on last click
12.   Poor quality of identifiers leading to inaccurate attributions
13.   The technology is constantly evolving and there are new attribution providers constantly coming up
14.   Data science talent needed- to apply increasingly sophisticated models.
15.   The attribution problem actually falls into 3 buckets (a) Cross channel attribution (Search, social, email etc.)(b) Cross platform (Phone, desktop etc.) and Offline attribution (footfalls, phone calls etc.)
16.   App Marketing  technology and tracking needs skilled resources and time. For instance- deeplinking needs skilled labour
 17. Tracking and then attributing results across channels in a cookie-less platform has been a challenge.


18.   There are 2 environments- Mobile web and Mobile app- each works in silos- lacks common tracking and varying degrees of functionality

Mobile Attribution guide - Part 3- General rules of attribution and priority

Rules of attribution and priority

























General rules of attribution and priority
1.Clicks takes precedence over impressions
2.Deterministic attribution 1:1 (unique identifiers, device IDs) takes precedence over non-deterministic non 1:1 (fingerprinting)
3.Clicks measured with a click date time take precedence over clicks measured without a click date time

4.When no deterministic identifiers are found then at last device fingerprinting method is used



Multi Touch Attribution- Assisted Installs and non Window conversions
In the last paragraph, we saw how we can credit an install to a network by using different methods. But that is not enough, we also need to understand how different ad networks or partners influenced the user before he finally downloaded the app. It also gives us an idea of the partner performance at individual level as well as to determine their reach
Below are some of the important terms:
Download- When user go to the app store and downloads the app into his device
Install- When the user opens the app for the first time
Attributed installs- Partner with last click and within the respective attribution window
Assisted installs- Prior to last click but within the attribution window
Non-window conversions- Partners with click within 30 days but outside of the attribution window

Example to understand Assisted installs +Non-window conv.






Example Scenario to understand the above
Partner 1- Click 20 days ago, attribution window 14 days
Partner 2- click 7 days ago, attribution window 7 days
Partner 3- Click 1 day ago, attribution 7 days ago
Detail: Here the attributed install goes to partner 1 as it is the last click and within the attribution window.Partner 2 receives the install assist as it generates clicks within their window. Partner 3 receives non window credit because their click was outside window but within the maximum 30 days

Mobile Attribution guide - Part 2 :-Mobile Attribution methods

Below are some of the methods currently used. There is no method which is the best, I will explain later in this article why I say so.

Before we proceed with the attribution, lets see how the attribution works , below is an example:


Example scenario- Click attribution window- 7 days

Here it takes 5 different channels(some repeated) over time for a user to finally convert. If the original display banner was not exposed to the user, he could have spent $1000 with any other competitor. every channel assisted in conversion someway or the other. Attribution gives a holistic view of the assisted and non assisted conversions.
For App install, we can see which network or partner actually helped to drive an install.

Conversion path
Display>Social>Search>Search>Direct

Available  Attribution models in Google Analytics- Last click, Last non-direct, Last adwords click, first interaction, linear, time decay and position based





Universal App Attribution Methods

Method 1: Google Install referrer method

Google Install referrer method
Attribution flow
1.User clicks on the ad run by one of the Ad network - &referrer= parameter with a unique click ID (ym_tracking_id) is appended to the link 
2.User is redirected to the attribution provider where referral and unique identifier is generated
3.It then moves to the Google play store , referral and unique identifier is also passed on
4.App downloaded> google adds referrer and identifier to the app
5.User open the app for the first time,SDK data and the database is matched
6.Attribution   is done as per the click data
Note:
(i) 1:1 accuracy -10% loss (ii) Supports customizable attribution window (iii)only click based attribution support (iv)Compatible only with Google play only, cannot track Android out of store


Method 2: Unique Identifier method



Attribution flow
1.User clicks on the ad run by one of the Ad network
2.When a user clicks the ad, the advertising network inserts various parameters in the tracking URL according to a template. One of these parameters is the device ID.Click is passed on to the tracker tool and is recorded with the device id bound to it
3.User is redirected to the play store
4.Downloads the app
5.When the user opens the app for the 1st time,, the tracking tool’s SDK collects the device identifier and send it to the app tracking tool platform with device identifier . Simultaneously the platform also receives an install request
6.The platform then searches for the clicks and installs that matches the description
7.Attributes the install to the partner based on this unique identifier. Any configurable postbacks are distributed
Note:
(i) 1:1 accuracy -10% loss (ii) Supports customizable attribution window (iii)Both click and impression  based attribution support (iv)Compatible only iOS and Android (v)Most common identifiers- Apple(IFA) and Google (AID) (vi)Not supported by all networks

Method 3- Device Fingerprinting method



Attribution flow
1.User clicks on the ad run by one of the Ad network
2.Click is passed on along with the data points to the tracker tool and is recorded. It collects the publicly available information from HTTP headers. Analytics platform creates a unique device fingerprint based in each click
3.User is redirected to the play store
4.Downloads the app
5.When the user opens the app for the 1st time,  the tracking tool’s SDK collects the same  data points and pass it to the analytics platform
6.The platform then searches for the clicks and installs with non-unique information and matches it with the
7.Attributes the install to the partner based on this unique identifier.
8.Any configurable postbacks are distributed
Notes:

(i) Least reliable method (ii)Data points- Platform, Device brand, Device model, Device carrier, IP Address, OS name, OS version, User agent, timestamp (iv) Non-changeable 24 hours attribution window(for some tools)(v)last click attribution

Method 4- Open URL with Click id method



Attribution flow
1.User clicks on the ad run by one of the Ad network. Tracker tool is notified about the click alng with the click id
2.As the app is previously installed, they go directly to the page on the banner- through deep linking
3.When the app is open, the SDK collects the open URL parameters including click_id
4.It then sends this to the App platform
5.Attribution Analytics platform takes the Click ID, finds the corresponding click record, and attributes the event to the click accordingly.
Notes:
(i)  Does not work for app installs. Only work if the app is previously installed (ii) Used for event tracking (iii) 1:1 accuracy (iv) It works for both app-to-app and web-to-app scenarios (v) offers customizable attribution window (vi) zero loss

Mobile Attribution guide - Part 1 : Attribution Modelling in Mobile World

Let's have a look on how attribution works

Attribution- Specifically talking about the Mobile, attribution refers to measurement of user events which  are the results of marketing activity. Or it can be defined as A method of assigning credit to a particular marketing interaction, brand touch point or channel in order to quantify the contribution   that are made by them towards a desired business goal (like Turnover, Profit, Customer retention, sales volume, revenue etc)
Examples- App Installs, product purchased(IAP), Level completion(in gaming), app launch etc

Traditional online advertising attribution techniques- Uses  (1) Cookies (2)Pixels(or tags) (3) Appended URL

Mobile attribution techniques/Universal Mobile App Attribution- (1) Google Install referrer (2) Identifier matching (3) Fingerprint MAtching (4)Open  URL with click id (many more are used like location tracking etc but these 4 are the major ones used by mobile tracking companies like Adjust, Appsflyer, MAT, Apsalar etc)
Mobile attribution is very complex if compared to the traditional attribution. For this presentation,  we will focus on Mobile attribution. First we will go through why attribution is needed through a sample conversion in the coming paragraphs/pictures (Major Players: Adjust, Apsalar, Appsflyer, Kochava, MAT/Tune etc)

There are several methods for attribution but it depends on 4 factors- Not all these can be tracked together through a single method (discussed in next slides)
1.Platform/App store- iOS/Apple iTunes  App Store, Android/Google Play Store, Amazon Appstore for Android, etc.
2.Engagement type- Click through vs View Through
3.Conversion type- Installs ve events


4.Flow - Web to app or App to App


Click Based Attribution
Install attribution is based on pre-determined timeframes which is also known as lookback windows. Below are some of the windows used in attribution
1.7- day standard- Network X serve the ads to user A. User A clicks on it within 7 day window, it will get the credit for that install (assuming that no other ad network is running ads simultaneously)
2.24 hour device fingerprinting attribution- Lets say if the device id or referrer is not available, the tracking is done using the device fingerprinting method. It can only record accurate data in very short window and hence the window is 24 hours
3.Facebook, Twitter and Google- Facebook- Fixed 28 days, Google- Fixed 30 days (non configurable window) while Twitter offers configurable windows of 1/7/14/30/90 days
4.Configurable window- Gives networks and advertisers great flexibility- networks need more window while advertisers can do an apple to apple comparison when running different ad networks under the same window. Its best used when we are running time bound campaigns

View through Attribution
Some agreements allows giving attribution credits even when ad is viewed and not clicked. Generally click is more powerful and it wins always. FB and Twitter charges on 24 hour window












Click Vs. Impression attributions?Winner?
Let's say , we are running campaigns with 2 different Ad networks. Network A has the click through window of 7 days and view through window of 1 day while Network B has only click through window of 15 days, no view through.
Here network B wins because it has the last click within the lookback window and also click wins over view even if it is within the window


In the next post, I will explain the different types of attributions used in the Mobile industry and how they work.

Ecosystem - Programmatic Buying

Below is how the Programmatic ecosystem works.

So let us understand how the programmatic buying works, below is an example of how the basic thing works out. The idea is to explain everything in pictures will minimal text (Click on the images to see a bigger size of it)


Programmatic Buying Basics















Advanced level view






























Basic definitions of Programming


















Decisions- Programmatic





















How Ads are prioritized in the server?
























Programmatic- Periodic table



Monday, 17 February 2014

Generate your own QR codes for free :)

Many of you must have seen those black and white QR codes and must be aware of it. Its very simple to use, you need to have a QR code reader installed to your smart phone. Just open your QR code reader, place your smart phone in front of ...and here you go ..... It opens ..

Have you ever wondered how you can make a QR code for yourself... Say you are a job seeker (Social media jobs) and want to impress your Potential employer , you can place a QR code on your resume and when once your potential employer clicks on , your video resume opens..Want to see this ?

Ok, so here we go.

 There are many tools that can help you, but today we will look at one of the simplest solutions available.... Go to www.qrstuff.com 

This screen opens , just select the 'Data type' Enter the content, select the look and feel and the content type.

Once you are done, just click generate.

When you click generate, you have your own QR code. Use it wherever you want and impress your peers and friends ...and your potential employers too :) 



Thursday, 30 January 2014

Video Resume




Sarang Kinjavdekar
Mobile +91-989 -956 -6188
Skype: sarangk82
Linkedin: http://in.linkedin.com/in/kinjavdekar



Core Strengths



Digital Marketing | Social Media | Digital planning and Strategy | Search Marketing | eCommerce | Website designing- UX and UI expert | Client Servicing and Account Management |Account/Project Planning | Integrated Marketing and Advertising | Online Brand Management | Online Reputation Management |Search Engine Optimization