kritter introduction - advertiser
TRANSCRIPT
Advertiser Business Case
Advertiser wants to promote its service/products to customers, using home grown online media buying platform
-- Why do it
-- Advantages
-- Timelines
-- Cost Comparison
-- Kritter Offering
Intellectual Property: Intellectual property is not ad-serving, RTB bidder, big data platform, Which most ad-tech companies claim. IP is when trade happens on these technologies and the learning to provide ROI. Ad-tech companies learn this by tweaking their system for large adv like you, and then use it as a solution to get your competitors to use their platformData: What platform, inventory/supply, targeting, how granular should the targeting be, what creativeswork, what time of day, what bid gets me the best traffic. That sliced by the products that you offer. That sliced by various stages of the user in the flow, registered, engagement, bought, repeat buy etc.. This is yourdata, correct use could lead to automating media planning and buyingProgrammatic: Budgeting, media planning, 100s of agencies globally, 100s of platforms globally, 1000s of supply sources, affiliate offers in house and third party, 100s of advertisers campaigns managers globally. Post buying measurement and analysis on excel sheets to arrive at next steps. This should be automated, providing your advertising team actionable data points, move them from low level to high level tasksCost Chain: Agencies charge 15% on of the media spend, platform charge 15%, ROI player (retargeting, CPA) charge the arbitrage of bid Vs CPA, Ad-network charge flat 50%. On an average only 60% of your media budget is actually spent on buying mediaVertical Integration: Basic economics, if online is your sales channel. If you have large teams globally managing marketing. Better control, full transparency, avoiding cost chain, a media buying system that is tightly integrated with your platform is the natural progression. Supply sources: Apart from keywords, which is company owned supply. All the other supply is with exchanges, or privately sold by premium publishers. All non exclusive supply sources will open up for a media buyers.
Business Case – Why do it
Media buyer-- Single DSP for all media teams globally-- Locally customized for relevance-- Knowledge center: Share and replicate learning local and global-- Integrated analytics: Automate, media budget, media planning, media buying, measurement.-- Supply sources: Exchanges, Premium/sites, Premium/Apps -- Retargeting: Targeted messaging to increase conversions-- Real-time conversion trending: something works accelerate it, something doesn't’t choke it-- Single platform for cross device marketing---------------------------------------------Outsourced media buyers-- Offline bidder: Integrate exclusive inventory platforms (ad-words) into the same decision engine-- Feedback bidder: Provide feedback to outsourced media buyers
Business Case - Advantages
Data!
Marketing KPIsPC:
-- Registration-- Engagement and user quality-- Credit card sync-- Transaction
Mobile:-- App Download-- Engagement and user quality-- Credit card sync-- Transaction
Milestones- Ad view, to click, to visit, to
Registration/Download to Transaction
- Transaction to repeat buy
Marketing parameters- LTV : Life time value (ARPU)- CPR/I: Cost per registration/Install- CPE: Cost per engagement- CPT: Cost per transacting customer- CPRU: Cost per repeat user
Customer Touch points:
-- Site/App
-- ISP
-- Device
-- Creative
-- On click landing page
-- User flow
Ad-tech system:
Campaign:
-- Budget
-- Bid
-- Ad, creative, landing page
Targeting:
-- Geo
-- Placement
-- Site
-- Device
-- OS
-- ISP
-- User/cookie
Supply:
-- Exchange
-- Site/App
-- Affiliate
-- Aggregator
Reporting:
Trade reporting sliced by all the parameters
Permutations and combinations sliced by billions of interactions.
Execution
Advertiser
Analytics
Google Ad words
Facebook Ads
Agencies
Aggregators
Ad Server Bidder
Exchanges
User
Engagement
Transactions
Decision Engine
Offline Bidder
Feedback Bidder
CRM
Publishers
DMP
Marketing Flow
Advertiser
Media Planning
Budget allocation
KPIs
Marketer
Platforms
Agencies
Your DSP
CRM Analytics
TAGS
Feedback
USER Interaction with Ads
U
Decision Engine
Landing Page
Components:DSP:• K – Ad-server (Programmatic)• K – Bidder (machine learning)• K – DP (Big Data)Customization:• Retargeting cookie technology• CRM integration• Decision engine• Creative Decision Engine (powered by user signals Vs engagement)• Landing Page Decision Engine (powered by user signals Vs engagement)• API integration to Platforms (Adwords)• White-labeled UI• Agency UI• Efficiency tool to be built around your marketing org
Recommended Software
Phase 1: DSP, with direct publisher and exchange buying. Migrate your media buying from other platformsTimeline: 60 daysDays 20: DeploymentDays 20: Exchange Integrations(Depending on the number of exchanges and their respective TAT)Days 20: Ready for campaign migration
Phase 2: CRM integration, KPI Module, Rule definition, and rule management system, Retargeting and cookie technologyTimeline : TBD
Phase 3: Decision engine: Targeting, Bid, Creative, Landing page. Across own DSP, External Platforms, and AgenciesTimeline: TBD
Phase 4: Business level access to algorithmic tweaking. Integrated analytics platform for analyzing and acting.Timeline: TBD
Phase 5: Knowledge center, auto generate case studies for sharing with regional teamsTimeline: TBD
Recommended Phases
Product Pricing: One-time price for a life-time license
Services: Charged on time spent• White labeling the product• Integrating the product with existing technology• Managing product roadmap• Business training and handover - Documentation• Technical training and handover - Documentation30 days: Acceptance period – Free30 days: Warranty period - Free
Maintenance:• Reactive Maintenance: Send an email to Kritter support and pay hourly charges for debugging (In case of client
having an existing technology team, wanting to manage tech operations)
• Proactive Maintenance: Monthly fixed charges to manage 24/7 tech operations and debugging of the software (In case of client having no technology team, wanting to outsource full tech operations
Enhancements: • Enhance patch: Kritter will keep releasing patches to enhance its software and will notify the customer of the new
features. Customer can pay a one time patch update price to acquire new features
• Enhancer retainer: Post delivery if the customer is looking at regular enhancement of the software. A pod will be built within Kritter to manage the road map of all developments, having a product manager, project manager, and engineers (based on work load). Patches included
Pricing Model
Kritter Product- Infrastructure cost 150mn Requests/day
Kritter Product- Infrastructure cost 1.5bn Requests/day
Kritter Vs. Appnexus (Rough Estimate)
Kritter!
Arjun Som: BE in Computer Science, GGSIPU.- Specializes in the set up of the direct sales, inside sales and online sales channels, customer acquisition, Org set up, and deep
understanding of start up execution- Worked in various roles in the digital marketing space, including affiliate, agency, demand, supply and network, in companies like
InMobi, Sapient, iGlobalMedia, and Indiaplaza- Leads Kritter’s business development, marketing, and over all PnLin.linkedin.com/in/arjunsom/
Kshitij Sooryavanshi: B.Tech., Computer Science, Indian Institute of Technology, Kanpur.- Specializes in core engineering, solving, machine learning, mathematical computing, algorithmic tasks, data mining, and predictive
modeling- Worked in companies like, InMobi, Vizexperts, Apache design solutions (acquired by Ansys)- Has varied experience in internet startup product development- Leads Kritter’s product line development, managing Programmatic buying and selling platformin.linkedin.com/pub/kshitij-sooryavanshi/31/b43/b64
Rohan Rai: B.Tech + M.Tech. (dual), Computer Science, Indian Institute of Technology, Delhi.- Specializes in data engineering, distributed data platform,big data and setting up data management platform- Experienced in start up domain having worked in early to large stages of InMobi, ZivaSoftware, Bizense, Qwest- Has varied horizontal experience in new age technology cutting across search, ops, dev ops, business rule management systems- Leads kritter’s data engineeringin.linkedin.com/in/rohanrai
Vikrant Chahar: B.Tech., Computer Science, Indian Institute of Technology, Guwahati.- Specializes in core engineering, solving ad serving, ad relevance, ranking, selection and market place dynamics- Worked in companies like, InMobi, Stratoshear, Globallogic, - Has varied experience in both software product and services- Leads Kritter’s product line development managing ad-servingin.linkedin.com/pub/vikrant-chahar/13/223/676
Founding Team
18-11-2014
Kritter Business Model
18-11-2014
Adv Consumer
Advertising / Technology Players
Inventory
$$
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Product and
Services
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Kritter is a pure play product and services company in the digital advertising space. Kritter provides industry players with highly customizable products and flexible services to run their digital business.
Kritter Products: Coded in-- DSP : Java-- Ad-server : Java-- Bidder: Java, Python, R, C++-- Data platform (Big Data): Pig
Kritter Services:-- Integrating above products into client’s stack-- Customizing Kritter products to fit client’s business needs-- Open up Kritter product modules, and integrate it to client’s technology-- Offshore outsourcing existing engineering tasks
Kritter - Solution
18-11-2014
-- Built a business model around enterprise ad-tech software-- Deploys products with source code on client’s stack-- Customizable products to fit business needs and client’s technology-- Experience in building high scale ad-tech -- Industry experience, to help streamline business customization and product roadmap-- Helps companies take new models to market with lightning speed-- All new technology requires a learning curve, specialized skill, and revenue risk to learn if it works. Kritter helps you de-risk!-- 80% of the software code has 20% of the trading impact, and 20% of the software code has 80% of the trading impact. Kritter products provide the 80% code right out of the box. Your engineers can focus on tweaking the 20% code impacting trade, using Kritter algorithms as a base model to improve upon. This keeps engineering team lean and high skilled. (Computational Mathematics/machine learning specialists and data scientists)-- Helps profit positive companies acquire technology keeping investments lean-- We are a start-up
Kritter - USP
K-DSP- Architecture
Agency
Agency
Dev
Adv
-CampaignSetup-Targe ng-Crea ves-Bid&Budget
Ad-Server
--AppandPlacementsetup-Margin-eCPMFloor-Adpreferences
Pub1
Pub2
Pub3
PubN--Eventtracking--Billing--InternalandExternalBidse ng--AdandSiteapproval--eCPMmaximizer
--Selec onandFiltering--CPM,CPC,CPIbilling
Bidder
Exng1
Exng2
Exng3
ExngN--CPMtoCPMbidding--CPCtoCPMbidding
Highlights:
• Integrate multiple supply sources: Websites, Applications, Exchanges, Aggregator, SSPs
• Campaign creation, budget management, bid management
• Ad creation, IAB standard creative format uploading, targeting
• Billing system to handle house clearing
• Reporting: Demand, Supply and Network statistics, along with saved queries
Key features:
APIs: Integrate any third party campaigns management or supply management tools with APIS. Build self serve UI and integrate it to the back end with APIs
Org Fitment: Customize the admin UI to superimpose your organization structure. This will allow you to set up access control across your ad-operations
Margin Management: Set budgets on the demand side by having internal and external bids and budgets. Set payout margins for publishers and eCPM floors to manage supply buying costs
Content Guidelines: Ad approval and site approval queue, whenever a new ad or site is created or existing ones are modified, this comes into the queue for approval. This ensures your content guidelines are maintained centrally, and your ad-ops team has a organized way of making sure what is going into the system to avoid irate advertisers and publishers
Hygiene setting: 4 types of hygiene mapping in the system. Premium, Family safe, performance, mature. To make sure the right set of ads are going onto the right set of inventory, and to maintain system hygiene.
Key Features - DSP
K- ad-server - Architecture
Campaign
Ad
Creative
Targeting
Predictive Analytics
Ranking Algo
Rich Media Serving
Feedback
Bidder Summary
Fraud Detection
Post Impression
Marketing KPI
Billing
Site/App
Exchange
Filters and Floors
Predictive Analytics
Clearing House
Revenue Max
Rich Media
Market Place
MarginsManual
Overrides
DMP
Highlights:
• Mobile and PC ad-serving :Banner, text, and, rich media ad delivery on exchanges and direct inventory
• Post impression tracking, attribution right up to conversion
• Conversion based pricing and selection, targeting manipulation on the fly for maximizing ROI
• Fraud detection and mitigation
• Connect multiple supply Sources, publishers, exchanges, aggregators, etc…
Key features:
Selection: Hundreds of advertisers, with hundreds of campaigns, thousands of ads, thousands of creatives and millions of permutation and combinations with targeting and placement preferences. The ad-server accommodates and automates.
Filtering: Advertisers want to be on some inventory and don't on some, they would like some categories and not like some, they choose granular targeting to ensure measurability across thousands of ads. Supply partners have brand protection clauses, anti competition ad-preferences, floor pricing, and house ads. The ad-server honors and automates all.
Ranking: Advertisers want acquisitions, the publisher wants eCPM and fill, while the network wants to make profits from all interactions. The ad-server has a unique ranking algorithm that automates optimization.
Key Features – Ad-server
K-Bidder - Architecture
Ad-server
Exchange -1
Exchange -2
Exchange -n
Adapter Integrations
Data Summaries
Algorithms
Campaign Budget
Campaign Details
Post Impression
DMP
Ad-serve Logs
Conversion
Win notification
Supply Forecasting
Price Landscape
OfflineBidding
CTR Prediction
Online Bid Adjustment
Risk Managemen
t
Highlights:
• RTB bidding across any number of exchanges
• Offline bid feedback provided to the online bidding agent to minimize server costs
• Single point management across hundreds of advertisers, thousands of campaigns, thousands of ads, and multiple exchanges. Keeping ROI and profits positive
Key features:
• Profit Maximization: Advertiser enters the max bid he is willing to pay for targeted traffic, while the exchange bid request keeps modifying over time. The Bidder component ensures it bids a value lower than the max bid, and for which traffic is available. This provides scale to and ensures profits for the network
• Supply Forecasting: Forecasts traffic against targeting granularity and combinations. Learning from interactions over time.
• Price Landscape: Predicts the price of the inventory, learning from interactions.
• CTR Prediction: Our bidder allows for your advertisers to bid on CPC while the bidder predicts CTR and bids on CPM on the exchanges.
• Risk management: Supply through exchanges is ever changing, interactions once positive could go into heavy losses in a matter of seconds. Kritter’s unique financial risk module, monitors and mitigates this.
Key Features - Bidder
K-DP - Architecture
Ad-serverSupply
ProductsDemand Products
Advertiser Publisher
Transport
Raw Data Store (Distributed Data System)
Processing
Transport
Fan Outs
HDFS
MySQLPropri
etyHive
Reporting API
Reporting Analytics Feedback
DMPs, Data Enricher,
Data Augmenters
Machine Learning
Highlights:
• Integrate with multiple logical boxes, like ad-serving, bidder, buy side, and sell side products. To transport and store data of various dimensions and granularity
• Fan outs/APIs: Pipe this data in to various front end products, like analytics, interface based query system, customer reporting. Pipe processed information into machine learning systems to empower various algorithms.
• Monitoring and alerting: Create various rules and processes to alert business and technology teams on anomalies and fluctuations.
• Processing: Create custom rules to process the raw data, integrate external DMPs to enrich data. The processing will keep in mind the varied outcome of the data needed for the business and technology
Key features:
• Big Data: This platform transitions with your business scale with seamless big data/distributed data infrastructure. Works on RDBMS, and when your data hits inflection point, can se ported into a Hadoopinfrastructure without any coding
• DMPs: Integrate external or home grown DMPs like bluekai, lotame, factual, etc to enrich ad-serving and bidding algorithms
• Customize: The DP can be customized to fit your business models like, hyper local, lat long, retargeting, UDID based serving, cookie technology
Key Features - DP
Product Pricing: One-time price for a life-time license• Business training and handover • Technical training and handover - Documentation30 days: Acceptance period – Free30 days: Warranty period - Free
Services: Charged on time spent• White labeling the product• Integrating the product with existing technology• Customizing client’s business model into the product
Maintenance:• Reactive Maintenance: Send an email to Kritter support and pay hourly charges for debugging (In case of client
having an existing technology team, wanting to manage tech operations)
• Proactive Maintenance: Monthly fixed charges to manage 24/7 tech operations and debugging of the software (In case of client having no technology team, wanting to outsource full tech operations
Enhancements: • Enhance patch: Kritter will keep releasing patches to enhance its software and will notify the customer of the new
features. Customer can pay a one time patch update price to acquire new features
• Enhancer retainer: Post delivery if the customer is looking at regular enhancement of the software. A pod will be built within Kritter to manage the road map of all developments, having a product manager, project manager, and engineers (based on work load). Patches included
Kritter Pricing
Thank Youwww.kritter.in
Enabling technology for advertising business
18-11-2014