This document provides an overview of the deep.bi analytics platform for ecommerce companies. It describes how deep.bi collects detailed ("deep") data on products, customers, and customer behaviors. This deep data is analyzed to provide real-time insights. Deep.bi helps ecommerce teams improve performance in areas like merchandising, marketing, customer service, and site experience. It does this by tracking custom metrics and providing customizable dashboards. Deep.bi can be used as a standalone tool or integrated with other systems through its API.
Building a 360 Degree View of Your Customers on BICSPerficient, Inc.
Why there is a need for Customer 360 and what the proposed cloud based solution is. We cover the stages of strategic marketing and how Oracle BI can help.
A Customer-Centric Banking Platform Powered by MongoDB MongoDB
Speaker: Alan Reyes Vilchis, Technical Lead, Banco Azteca
Level: 200 (Intermediate)
Track: Developer
Business apps powered by single customer views (SCV’s) are one of the most predominant uses of MongoDB. However, each view presents unique challenges such as distilling data from providers, removing duplication, matching records in different systems, and more.
The team at Banco Azteca (part of Grupo Salinas, a holding company of enterprises in media, telecommunications and financial services) in Mexico City has launched various customer-centric banking services that are powered by an SCV built on MongoDB, which has not only allowed the expansion into mobile-first consumer markets, but has also helped in identifying and preventing fraud across the group’s enterprises. This talk will explore the overall initiative, and place emphasis on the technical innovations regarding design, serialization and transactions across multiple systems.
What You Will Learn:
- “Serialization magic” using the MongoDB Java driver and Jackson
- Implementing transactional-like logic across different systems
- Conceptual and physical design for building a Single-View
The role of Big Data and Modern Data Management in Driving a Customer 360 fro...Cloudera, Inc.
Organizations spanning all industries are in pursuit of Customer 360, which aims to integrate and enrich customer information across multiple channels, systems, devices and products in order to improve the interaction experience and maximize the value delivered. To achieve this real-time integration requires a modern approach to working with data and the Cloud is providing a differentiating strategic platform for many organisations. Discover how you can strategically structure your data environment leveraging the Cloud to empower analytical deployment, create next generation customer applications whilst also saving costs and realising greater efficiencies.
The Connected Consumer – Real-time Customer 360Capgemini
With Business Data Lake technologies based on EMC’s Big Data portfolio it becomes possible to move away from channel specific analytics towards a 360 customer view.
This presentation will show how technologies like Spark, Hadoop, and Kafka help companies gain a real-time view of everything their customers do and make changes to customer touch points whether mobile, web, in-store, direct marketing or existing transactional systems.
Presented by Steve Jones, Vice President, Insights & Data, Capgemini at EMC World 2016
http://www.capgemini.com/emc
Building a 360 Degree View of Your Customers on BICSPerficient, Inc.
Why there is a need for Customer 360 and what the proposed cloud based solution is. We cover the stages of strategic marketing and how Oracle BI can help.
A Customer-Centric Banking Platform Powered by MongoDB MongoDB
Speaker: Alan Reyes Vilchis, Technical Lead, Banco Azteca
Level: 200 (Intermediate)
Track: Developer
Business apps powered by single customer views (SCV’s) are one of the most predominant uses of MongoDB. However, each view presents unique challenges such as distilling data from providers, removing duplication, matching records in different systems, and more.
The team at Banco Azteca (part of Grupo Salinas, a holding company of enterprises in media, telecommunications and financial services) in Mexico City has launched various customer-centric banking services that are powered by an SCV built on MongoDB, which has not only allowed the expansion into mobile-first consumer markets, but has also helped in identifying and preventing fraud across the group’s enterprises. This talk will explore the overall initiative, and place emphasis on the technical innovations regarding design, serialization and transactions across multiple systems.
What You Will Learn:
- “Serialization magic” using the MongoDB Java driver and Jackson
- Implementing transactional-like logic across different systems
- Conceptual and physical design for building a Single-View
The role of Big Data and Modern Data Management in Driving a Customer 360 fro...Cloudera, Inc.
Organizations spanning all industries are in pursuit of Customer 360, which aims to integrate and enrich customer information across multiple channels, systems, devices and products in order to improve the interaction experience and maximize the value delivered. To achieve this real-time integration requires a modern approach to working with data and the Cloud is providing a differentiating strategic platform for many organisations. Discover how you can strategically structure your data environment leveraging the Cloud to empower analytical deployment, create next generation customer applications whilst also saving costs and realising greater efficiencies.
The Connected Consumer – Real-time Customer 360Capgemini
With Business Data Lake technologies based on EMC’s Big Data portfolio it becomes possible to move away from channel specific analytics towards a 360 customer view.
This presentation will show how technologies like Spark, Hadoop, and Kafka help companies gain a real-time view of everything their customers do and make changes to customer touch points whether mobile, web, in-store, direct marketing or existing transactional systems.
Presented by Steve Jones, Vice President, Insights & Data, Capgemini at EMC World 2016
http://www.capgemini.com/emc
Big Data Done Right by Successful OrganizationsEuro IT Group
Euro IT Group can help you unlock the tones of information already flowing through your organization, analyze it, extract value and transform it into insight that drives growth and revenue. Furthermore, by going through one of our big data quick wins programs, you will be able to enjoy the benefits of big data extremely fast, test and validate big data technologies and make better strategic decisions for managing your overall company data; our quick win program enables you to enjoy quickly new insights and measurable results by putting at work your existing data streams and to test and validate Big Data Technologies that can complement your legacy BI / DWH infrastructure.
Webinar: Increase Conversion With Better SearchLucidworks
Hear from IBM Product Line Manager Iris Yuan & Lucidworks VP of Partner Engineering Sarath Jarugula for a deep discussion into how improving ecommerce search can drive conversions and increase revenue.
The concept of a 360° view, especially of customers, although it potentially applies to other things too, has been around for a substantial period of time. The idea behind the 360° view of customers is that the more you know about your customers the easier it will be to meet their needs, both in terms of products and aftersales care, and to market additional goods and services to them in the most efficient fashion. Thus a 360° view helps both in terms of customer retention and acquisition, as well as up-sell and cross-sell.
In this presentation which complements Bloor Whitepaper on the "Extended 360 degree view" we will discuss why we believe that extending the traditional 360° view makes sense and we will give some uses that demonstrate why the extended 360° view represents an opportunity, both for those that have already implemented a 360° view and for those that have not.
Samsung’s First 90-Days Building a Next-Generation Analytics PlatformCloudera, Inc.
Leveraging in-memory processing for advanced analytics paired with rich data visualization for business intelligence, Samsung is creating a flexible and scalable next-generation analytics platform built on Cloudera Enterprise.
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Accelerate Actionable Insights with the Business Data LakeCapgemini
"Insight driven" EMC Federation Business Data Lake realizes Big Data value.
Learn how founders Capgemini and Pivotal build and use the Business Data Lake to rapidly deploy, scale, integrate and implement new insights into building better systems and business performance.
Discover how real companies in finance, automotive, manufacturing, travel, and oil & gas use these insights to transform their businesses.
First presented at EMC World 2015.
Oracle Endeca 101 Developer Introduction High Level OverviewGordon Kiser
This slideshare gives developers a high level overview of the structure of an Oracle Commerce Experience Manager page used by business users to create scenarios and triggers that may control static pages and dynamic pages that automatically present content based on site visitor behavior.
Endeca: Developing A Best Practice Search ExperienceDay Software
Search and browse pages are where customers decide whether your site can meet their needs. The best sites quickly guide customers to the best products and information that match those needs. But which user experience elements are most effective in pushing customers to a purchase? Learn best practices for developing a search experience that converts more visitors into customers.
Rob Swint, Director of Product Marketing, eBusiness solutions, Endeca
Big Data Done Right by Successful OrganizationsEuro IT Group
Euro IT Group can help you unlock the tones of information already flowing through your organization, analyze it, extract value and transform it into insight that drives growth and revenue. Furthermore, by going through one of our big data quick wins programs, you will be able to enjoy the benefits of big data extremely fast, test and validate big data technologies and make better strategic decisions for managing your overall company data; our quick win program enables you to enjoy quickly new insights and measurable results by putting at work your existing data streams and to test and validate Big Data Technologies that can complement your legacy BI / DWH infrastructure.
Webinar: Increase Conversion With Better SearchLucidworks
Hear from IBM Product Line Manager Iris Yuan & Lucidworks VP of Partner Engineering Sarath Jarugula for a deep discussion into how improving ecommerce search can drive conversions and increase revenue.
The concept of a 360° view, especially of customers, although it potentially applies to other things too, has been around for a substantial period of time. The idea behind the 360° view of customers is that the more you know about your customers the easier it will be to meet their needs, both in terms of products and aftersales care, and to market additional goods and services to them in the most efficient fashion. Thus a 360° view helps both in terms of customer retention and acquisition, as well as up-sell and cross-sell.
In this presentation which complements Bloor Whitepaper on the "Extended 360 degree view" we will discuss why we believe that extending the traditional 360° view makes sense and we will give some uses that demonstrate why the extended 360° view represents an opportunity, both for those that have already implemented a 360° view and for those that have not.
Samsung’s First 90-Days Building a Next-Generation Analytics PlatformCloudera, Inc.
Leveraging in-memory processing for advanced analytics paired with rich data visualization for business intelligence, Samsung is creating a flexible and scalable next-generation analytics platform built on Cloudera Enterprise.
Big Data, IoT, data lake, unstructured data, Hadoop, cloud, and massively parallel processing (MPP) are all just fancy words unless you can find uses cases for all this technology. Join me as I talk about the many use cases I have seen, from streaming data to advanced analytics, broken down by industry. I’ll show you how all this technology fits together by discussing various architectures and the most common approaches to solving data problems and hopefully set off light bulbs in your head on how big data can help your organization make better business decisions.
Accelerate Actionable Insights with the Business Data LakeCapgemini
"Insight driven" EMC Federation Business Data Lake realizes Big Data value.
Learn how founders Capgemini and Pivotal build and use the Business Data Lake to rapidly deploy, scale, integrate and implement new insights into building better systems and business performance.
Discover how real companies in finance, automotive, manufacturing, travel, and oil & gas use these insights to transform their businesses.
First presented at EMC World 2015.
Oracle Endeca 101 Developer Introduction High Level OverviewGordon Kiser
This slideshare gives developers a high level overview of the structure of an Oracle Commerce Experience Manager page used by business users to create scenarios and triggers that may control static pages and dynamic pages that automatically present content based on site visitor behavior.
Endeca: Developing A Best Practice Search ExperienceDay Software
Search and browse pages are where customers decide whether your site can meet their needs. The best sites quickly guide customers to the best products and information that match those needs. But which user experience elements are most effective in pushing customers to a purchase? Learn best practices for developing a search experience that converts more visitors into customers.
Rob Swint, Director of Product Marketing, eBusiness solutions, Endeca
Ripple Labs @DeveloperWeek: Building the Payments WebRipple Labs
Building the Payments Web is a half-day of discussion and idea-sharing about the movement to re-architect payments for the Internet using math-based currency protocols, so that, for the first time in history, they’re globally inclusive. Attendees will hear from pioneers of the payments space, learn about the Bitcoin and Ripple protocols, and pitch their ideas to compete for XRP prizes. The event is hosted by Ripple Labs, the creators of the Ripple protocol.
Rethinking Finance as a spot and future contingency management system for assets and liabilities. Blockchains are an improved form of contingency management (precision, automation, lower-risk). The Internet transfers information, and now value; the Internet becomes a contingency management system with programmable money, smart contracts DACs, distributed ledger transactions. Ultimately, blockchain financial networks can automatically and independently confirm and monitor transactions, without central parties like banks or governments.
A Complete Beginners Guide to Blockchain Technology Part 3 of 6. Slides from the #StartingBlock2015 tour by @blockstrap
Part 1: http://www.slideshare.net/Blockstrap/cbgtbt-part-1-workshop-introduction-primer
Part 2: http://www.slideshare.net/Blockstrap/02-blockchains-101
Part 3: http://www.slideshare.net/Blockstrap/03-transactions-101
Part 4: http://www.slideshare.net/Blockstrap/cbgtbt-part-4-mining
Part 5: http://www.slideshare.net/Blockstrap/05-blockchains-102
Part 6: http://www.slideshare.net/Blockstrap/06-transactions-102
Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...
The slide deck we used to raise half a million dollarsBuffer
This is the pitchdeck we used to raise half a million dollars from Angel investors. More here:
http://onstartups.com/tabid/3339/bid/98034/The-Pitch-Deck-We-Used-To-Raise-500-000-For-Our-Startup.aspx
How To Pick The Best Analytics Tools: Product Analytics Landscape
Here, we’ll talk about assessment criteria, key features, and greater for deciding on systems and gear that match your enterprise app development desires.
Choosing the right solution for your data
Because massive facts apply to the sort of huge spectrum of use app development instances, packages, and industries, it’s difficult to nail down a definitive listing of choice criteria.
Types of data analytics tools & key features
What is the gear used for massive facts analytics? Data analytics tools gear constitute a huge category, though they have a tendency to fall into some key groups.
Customer data platforms
Customer data platforms like customer relationship management platforms (CRM) seize purchaser facts that may be used to enhance strategies or promote products. However, CDPs take matters to the following level.
Core capabilities:
• 360-diploma view of the purchaser.
• Connect more than one fact source.
• Unifies purchaser facts throughout all linked structures.
• Improve concentrated on for advertising campaigns.
Business intelligence (BI) tools
Today’s business intelligence (BI) assists companies to see iOS app development and apprehend facts. According to gartner, BI gear span 3 major categories. Online analytical processing, or OLAP, permits fact discovery, ad-hoc reporting, simulation fashions, overall performance control, and different complicated evaluation abilities. There’s additionally statistics transport–which serves up insights within the shape of visualizations, reports, and dashboards. And finally, BI integration–which offers metadata control and imparting app developers surroundings to assist your method.
Core capabilities:
• Data visualization.
• Predictive modeling.
• Data mining.
• Forecasting.
Customer analytics tools
Customer analytics is designed to control the overall analytics technique from guidance to perception generation. In maximum instances, purchaser analytics systems include web development pre-built facts fashions for forecasting, propensity to buy, and numerous statistical evaluation strategies to apprehend purchaser conduct and optimize products, offerings, and reports.
Core capabilities:
• Granular segmentation.
• Customer satisfaction Insights.
• Statistical modeling.
• Acquisition, retention, & churn metrics.
Digital experience platforms
Digital experience platforms is a new kind of enterprise-grade software development designed to optimize the purchaser revel in at each touchpoint. While DXPs overlap with purchasers revel in control systems, DXPs cognizance greater on streamlining strategies, coordinating and personalizing content material to customers throughout an extensive variety of channels which include the Internet of Things (IoT), virtual assistants, VR reports, and greater.
Core capabilities:
• API-first structure.
• Multi-touchpoint control.
• Dynamic templates for automating personalization.
• Content control and transport.
Business Objectives that analytics can achieve is Resource allocation,
Customer segmentation, competitive benchmarking, customer facing.
Speaker: Shailender Mathur, SVP, Progressive
Big Data Explained - Case study: Website Analyticsdeep.bi
This is an example case study showing what big data can mean for a small website that generates just 5000 visits a day.
It all depends on what we want do get from our assets like website traffic. If we only measure the number of people who visited our site, then we do not need to worry about “big data”. We just have to count total visits (5000 a day, 150 000 monthly).
But by using just the simple measure we know nothing about our visitors / customers. So, it pretty useless.
On the following slides we present what a website owner can gain from advanced website analytics and why big data technologies are recommended.
Big data is an opportunity for communications service providers (CSPs) to create the intelligence for operating their infrastructures more efficiently, to analyze the success of their services, and to create a better personal experience for their customers.
CSP Top executives, Network and IT managers and Marketing, are eager to exploit the large amount of information to achieve better business decisions. They expect their Chief Technical Officer to provide end-to-end analytic solutions based on the data available in their IT and network infrastructure.
This presentation analyzes the complete value chain that can transform CSPs’ data to knowledge. It covers the sources of information, the data collection tools, the analytic platforms providing quick data access, and finally the business intelligence use cases with the presentation and visualization of the results and predictions.
Insurance - Open Source Analytics Dashboards for Real Time Business OverviewEuro IT Group
Check this Slide Deck to understand how open source analytics dashboards can support better strategic decisions. Such dashboards can be available in a matter of hours if data is available within your systems. If not, we can make it available.
“In today’s digital world, businesses that want to master the flow of information have to address three key challenges: the explosive growth in data volumes, the need to analyse those growing volumes in real-time, and the need to deliver the resulting insights to users...” ‘Insights Everywhere’ Intel White Paper
Cygnet developed a comprehensive cloud based SaaS solution based on Microsoft SQL server capabilities and Microsoft Business Intelligence (MSBI) tools. Cygnet also provided rich web and mobile based analytics solution to collect and analyse EDI 852, POS, and supply chain data.
How to build a Single View of Customer using his Digital Journey across multiple channels & multiple assets?
Presented at Big Data & Analytics Innovation Summit, Singapore, 2018
[Notes] Customer 360 Analytics with LEO CDPTrieu Nguyen
Part 1: Why should every business need to deploy a CDP ?
1. Big data is the reality of business today
2. What are technologies to manage customer data ?
3. The rise of first-party data and new technologies for Digital Marketing
4. How to apply USPA mindset to build your CDP for data-driven business
Part 2: How to use LEO CDP for your business
1. Core functions of LEO CDP for marketers and IT managers
2. Data Unification for Customer 360 Analytics
3. Data Segmentation
4. Customer Personalization
5. Customer Data Activation
Part 3: Case study in O2O Retail and Ecommerce
1. How to build customer journey map for ecommerce and retail
2. How to do customer analytics to find ideal customer profiles
The ideal customer profile in a B2B context
The ideal customer profile in a B2C context
3. Manage product catalog for customer personalization
4. Monitoring Data of Customer Experience (CX Analytics)
CX Data Flow
CX Rating plugin is embedded in the website, to collect feedback data
An overview of CX Report
A CX Report in a customer profile
5. Monitoring data with real-time event tracking reports
Event Data Flow
Summary Event Data Report
Event Data Report in a Customer Profile
Part 4: How to setup an instance of LEO CDP for free
1. Technical architecture
2. Server infrastructure
3. Setup middlewares: Nginx, ArangoDB, Redis, Java and Python
Network requirements
Software requirements for new server
ArangoDB
Nginx Proxy
SSL for Nginx Server
Java 8 JVM
Redis
Install Notes for Linux Server
Clone binary code for new server
Set DNS hosts for LEO CDP workers
4. Setup data for testing and system verification
Part 5: Summary all key ideas
Big Data Paris - A Modern Enterprise ArchitectureMongoDB
Depuis les années 1980, le volume de données produit et le risque lié à ces données ont littéralement explosé. 90% des données existantes aujourd’hui ont été créé ces 2 dernières années, dont 80% sont non structurées. Avec plus d’utilisateurs et le besoin de disponibilité permanent, les risques sont beaucoup plus élevés.
Quels sont les paramètres de bases de données qu’un décideur doit prendre en compte pour déployer ses applications innovantes?
Google Analytics is the most popular web analytics system. Almost every webpage, whether it’s a private blog or large e-commerce site, uses Google Analytics. This session will cover essential information about Google Analytics and its API guidelines, competitors, and most important, how you can use the data from such offerings together with your ERP, CRM, and other OLTP systems. You will see how to load Google Analytics data using SQL Server Integration Services, for example, and merge that data with your local data. In addition, we will walk through a demonstration of important web analytics KPIs and how you can analyze them using Microsoft Business Intelligence tools
Similar to Deep.bi - Real-time, Deep Data Analytics Platform For Ecommerce (20)
2. Every business is different
So, there’s no “one-size-fits-all”
analytics solution
3. Deep.bi is a real-time,
deep analytics platform
It helps ecommerce teams
improve their performance by providing
current and precisely tailored insights.
4. Operational excellence and performance
Category Managers / Merchandisers
Find new revenue opportunities, improve
rotation, promote best sellers, eliminate
non-sellers, up-sell, cross-sell.
Marketers
Deeply understand your customers and
what brings them to purchase. Then
optimize your marketing spent across
markets and channels.
Customer service
Maintain more personalized customer
relationships. Fulfill customer needs based
on their value.
UX / Design Team
Improve your site constantly by micro-
updates and monitor their impact on
conversion in real-time.
Tech / IT
Monitor site performance. Quickly deliver
new reports and functionalities. Focus on
business value, outsource heavy
engineering stuff to experts.
Executives / Managers
Get the up-to-date big picture of your
store performance. Monitor key metrics
like conversion rate, revenue, retention in
real-time.
6. Historic data
is excellent for
strategy and planning.
Real-time data
gives the right,
current context
and helps take
action intraday
to improve
daily profits.
Is real-time
data useful
in ecommerce?
7. People are complex.
We make decisions
based on many
factors.
deep.bi helps extract
product, customer
and behavior
detailed attributes
to find real
purchase patterns.
What’s
deep data
and why
it’s important?
8. Example of tracked product dimensions:
• Name
• Brand
• SKU
• ID
• Offer Price
• Regular Price
• Save Amount
• Availability
• Specs
• Weight
• Color
• Size
• Box Size
• categories
Deep data: Product
Deep.bi extracts detailed
product characteristics and
make it available for analysis
with all other data.
Example insights:
• Most viewed but unavailable products
by brand
• Worst selling shoes by color
• Worst selling smartphones by battery
life, weight and size
• Top selling at full price Nike men
running shoes in California by detailed
features (size, color, weight)
9. Deep data: Customer
Example of tracked user dimensions:
• User
• Cookie
• Email
• First Name
• Last Name
• Gender
• Location:
• ZIP
• City
• Region
• Country
• Population
• Device
• Type
• Brand
• Model
• Version
• Internet Provider
• Type
• Name
Deep.bi can enrich raw user
data (like IP) with rich,
business-useful information.
That allows to deeply
understand customers and
prospects. By combining this
data with behavior and product
data, store managers can
optimize marketing spend,
traffic sources and inventory.
10. Deep data: Behavior
Example of tracked event behavior dimensions:
• Event Type
• Timestamp
• URL
• Referrer Host
• utm_source
• utm_campaign
• utm_mediium
• Active Engagement Time
By knowing detailed
characteristics of users’
behaviors ecommerce
managers can build detailed
users profiles, discover patterns
and track key metrics like:
• RFM (Recency, Frequency, Monetary),
• LTV (Customer Lifetime Value)
• CAC (Cost of Acquiring Customer)
• AOV (Average Order Value)
• COS (Cost of Sale – Ad Spend /
Revenue)
• Shopping Cart Abandonment
Track any important user behaviors like:
• product views
• adding items to cart or wish list
• purchases
• delivery confirmations
• newsletter subscription
• return request and any other.
Measure detailed behavior characteristics,
like active engagement time while reading
product descriptions.
11. Find deep buying
patterns and
correlations
Example: what buy and how behave people
from small cities who use iPhone and came
from Facebook and what product features are
important for them, etc.
Adjust prices and
optimize stock
Track best-sellers in real-time, optimize price
to maximize profits. Find non-sellers and
features that are common for them (maybe
brand, color, size, etc.)
Predict
Having collected detailed, raw and enriched
data you can build customer predictive models
using machine and deep learning algorithms.
Combining
deep data with
real-time
insights
creates
unprecedented
possibilities
12. deep.bi can be used standalone or
as a part of your current solutions
deep.bi
dashboards
Use our predefined
dashboards and
metrics or customize
them to fit your needs.
deep.bi
API
Use API to build your
own, external
dashboards or embed
our analytics in your
current systems.
deep.bi
data platform
Use deep.bi as a data
collector and enricher
to build your
customized solutions,
e.g. prediction system
13. Quick and easy
to implement
Minutes/hours vs. weeks or months. Just
embed our script and start tracking.
Real-time
Data latency <1s
Super-fast
Less than a 1s on TB-size data store
Scalable
Petabytes and more
Highly flexible
No relational data modeling
(schema-flexible), no data pre-aggregation,
no defining reports up front. Just dig into data
and explore it. Add new dimensions (columns)
and metrics on the fly.
Why deep.bi
is unique?
(technical explanation in blue)
16. More analysis examples
Merchandising insights:
• Product, SKU, Category, Brand Report:
views, added to cart, sold, CR, etc.
• Hot Products (most viewed, most
added to wish lists, most added to
carts)
• Non sellers, cold products
• Most discounted products
Lifecycle marketing:
• Who viewed but did not purchase
• 30/60 day repeat purchase rate
• Best products/categories/brands for
repeat purchase
• Products/categories purchased
together
• Customer Lifetime Value by channel
(day 1, 90, 180, 360)
Conversion & performance:
• Purchase funnel incl. abandoned cart
• Conversion & attribution by traffic
source/referral, campaign
Customer intelligence:
• Best customers by detailed
characteristics (demographics, RFM,
best full price customers, etc.)
• Cold customers: not buying, low AOV
• Customer Lifetime Value (Day 30, 90,
180, 360)
• How long it takes customers to
purchase
UX improvements
• Checkout improvement: find that most
customers are abandoning carts when
they reach a confusing section in your
checkout process that you were not
even aware of.
20. Enrich web data with business information
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AppleWebKit/537.36 (KHTML, like Gecko) Chrome/42.0.2311.152 Safari/537.36",”[url_hidden]",
7279848891,@906,"https://www.google.pl/",vuser-history-allegro-1-
hc20150509.1,"122_100003_Park@700:html_620x100_single_banner:See offer"
IP, URL, cookie, user-agent, timestamp, text…
Raw, web browsing data
Real-time data enrichment
Structured data
Enriched data
see the next slide
21. * Coming soon
Get deeper insight - enrich raw user data
50+information
from one
interaction
Purchase intent
Device
Time
Location
ISP
Online context
Weather*Demographics
22. User location details
Example use:
• international travellers
• townspeople
• people in mountains
• rainy day
• Country
• Region
• City
• ZIP Code
• Population
• Latitude & Longitude
• Time zone
• IDD prefix to call the city from
another country
• Phone area code
• Mobile Country Code (MCC)
• Mobile Network Code (MNC)
• Elevation
• Weather at the moment of event
23. Business context based on internet provider
Example use:
• [telco] competitors’ users-
> acquisition
• [telco] our users ->
retention/up-selling/cross-
selling
• people from particular
company or company type
• ISP name or Organization name
• Organization type:
• Commercial
• Organization
• Government
• Military
• University/College/School
• Library
• Content Delivery Network
• Fixed Line ISP
• Mobile ISP
• Data Center/Web Hosting/Transit
• Search Engine Spider
• Reserved
• Mobile brand
• Net speed
24. Detailed information about user’s device
Example use:
• smartphone users
• Apple users
• Samsung Galaxy users
• Google browser users
• Device Type
• Device Brand
• Device Model
• Device Operating System
• Operating System Producer
• Browser
• Browser Producer
26. • Deep.BI provides two ways of ingesting data: using direct
REST API or through JavaScript snippet.
• In both ways data is sent in JSON format.
• Deep.BI is event-based analytics what means that we collect
full scope of information about every single tracked event
that happens on your site.
• We provide full flexibility of defining data dimensions:
• You can define as many dimension as you want (e.g. 100+
dimensions for every event)
• You can build infinite hierarchy of dimensions, e.g.:
product.specification.size.width.unit, or category.category.category…
• On the following slides we provide some examples of data
dimensions for: product, user and user behavior.
Deep.bi Data Ingestion API
No two businesses are the same. Even if you sell the same kind of products or services, you and your competition have different marketing approaches, product presentations, store design, target demographics, brand loyalists, ethics on how the company is run, and employees.
optimizing acquisition channels (revenue growth, reducing marketing costs)
buying and selling the right products at the right time
servicing customers (returns, delivery)
better understanding customers’ behavior to engage them
Ecommerce real-time analysis examples:
Monitor intraday revenue targetsYou can act instantly when sales goals are below the expected level for example by blasting an email campaign or buying traffic.
Optimize acquisition channels (referral traffic)Stop wasting money for low quality traffic/campaigns. Test channels and campaigns variations and shift budget to the best performers.
Sell and promote the right productsOccasionally you’d want to focus your sales on particular products, category or brand. Monitor in real-time these special actions and make improvements to maximize profits.Also, watch real-time trends to boots promotion of the top selling products.
Conversion ratesUnderstand how minor changes, social media promotions, email newsletters affect your conversions in real time.
Impact of website updatesGet to know when to apply changes to your store (lowest traffic) as well as monitor in real-time how the updates affect your metrics (sometimes errors happen – know it instantly!).