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PERSONALIZATION &
OMNICHANNEL
EXPERIENCE
SHIFT.COLOMBUS-CONSULTING.COM
3
Agenda
Challenges for organizations and ecosystem complexity
... And can AI save Marketers?
... But how to ensure a UX c...
4
A Personalized relationship: the strongest
consumers expectation!
5
Which objectives for UX Personalization?
O P T I M I Z E U X
S AT I S F Y
D E V E L O P
R E TA I N
S E R V E
C O N V E R...
6
D ATA C O L L E C T I O N
#1 Anticipate customer needs through personalization
1st party data
The user is watching « mat...
7
D ATA A C T I VAT I O N
Segment « prospect | mature skin » identified on Brand site
>> banner « -20% on Mature skin prod...
8
D ATA A C T I VAT I O N
Segment « prospect | mature skin » identified on Brand site
>> banner « -20% on Mature skin prod...
9
#2 Propose a relevant offer for a Customer with clear needs
D E V E L O P
N.B: use cases are purely illustrative
D ATA C...
10
#2 Propose a relevant offer for a Customer with clear needs
N.B: use cases are purely illustrative
D ATA A C T I VAT I ...
11
… and a performance that follows the consumers adoption
TEST EVOLUTION
A/B/n & MVT Testing Segmentation
& Targeting
Per...
12
... But how to ensure a UX coherence with
omnichannel?
13
For an omnichannel experience, organization silos must collapse
Connected
Boutique / IoT
Web / Mobile /
App
Pub Social ...
14
5 pillars for a (truly) omnichannel personalization
UX
SOLUTION ECOSYSTEM
DATA
ORGANIZATION & GOVERNANCE
INTELLIGENCE
15
Moving from a Channel-centric to a Customer-
centric organisation
Multi-channel
Channel-centric Customer-centric
Omnich...
16
An Agile Toolbox for scoping and management
PERSONAE
From customers to
real life personae
A Persona represents a person...
17
« Design by Data » approach for improving UX
4
Business
insight
Behavior analysis AB testing Web, app, email …
optimisa...
18
An acceleration of available data from various
channels (digital & offline)
EARNED PAID
OWNED
e-mail
twitter
partners
b...
19
Data Marketing maturity model: omnichannel &
real time Marketing as a target
Customer
experience
maturity
Implementatio...
20
A simple architecture from data to activation
Collect & Analyse Target Activate
Inidividual & anonymous data Audience &...
21
But numerous apps for targetting & activating…
Target Activate
Online
Offline
CRM
Media / RTB Social ads
Web / Mobile
T...
22
Data Marketing solutions with various objectives
CRM SFA
DCO
DMP
(media & CRM centric)
DMP
Social CRM
Testing / Perso
O...
23
GDPR impact: challenge or opportunity?
Editors need to facilitate these new requirements ... and brands need to check t...
24
Lost with Data Marketing ecosystem?
25
The Digital Benchmark as a first and quick answer
http://www.thedigitalbenchmark.com/
26
The Digital Benchmark | categories
Ad Verification & Brand Safety
Ad-Server
Affiliate Management
Demand Side Platform (...
27
Return on experience
28
Key learnings when building your ecosystem
Mobile
Media / Channel
Attribution
Unicity
Cross-device
journey
> Test mobil...
29
#AI (Artificial Intelligence): some clear expectations, but some
clear gaps in omnichannel mode
Deep Learning
on fans
b...
30
Embark Business prioritires, the organization, archietcture
constriantes in order to define a target ecosystem
LEGAL
(!...
31
QUESTIONS?
32 digitbench18WIFI digitbench18 #
CONTACT
JEAN MENEVEAU
Partner
meneveau@colombus-consulting.com
+33 6 50 73 60 99
33 #
THANK YOU
FOR YOUR ATTENTION
Omnichannel Personalisation & UX: how to build an integrated Data Marketing ecosystem? - Colombus Consulting Shift - Bench...
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Omnichannel Personalisation & UX: how to build an integrated Data Marketing ecosystem? - Colombus Consulting Shift - Benchmark by EBG Barcelona 2018

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Omnichannel Personalisation & UX: how to build an integrated Data Marketing ecosystem? - Colombus Consulting Shift - Benchmark by EBG Barcelona 2018

  1. 1. PERSONALIZATION & OMNICHANNEL EXPERIENCE SHIFT.COLOMBUS-CONSULTING.COM
  2. 2. 3 Agenda Challenges for organizations and ecosystem complexity ... And can AI save Marketers? ... But how to ensure a UX coherence with omnichannel? Omnichannel approach: the holy grail!
  3. 3. 4 A Personalized relationship: the strongest consumers expectation!
  4. 4. 5 Which objectives for UX Personalization? O P T I M I Z E U X S AT I S F Y D E V E L O P R E TA I N S E R V E C O N V E R T
  5. 5. 6 D ATA C O L L E C T I O N #1 Anticipate customer needs through personalization 1st party data The user is watching « mature skin » videos 2nd party data Visit on comparative Cosmetics sites 3rd party data Female 50-65 yo Segment: « prospect | mature skin » N.B: use cases are purely illustrative enrichment C O N V E R T
  6. 6. 7 D ATA A C T I VAT I O N Segment « prospect | mature skin » identified on Brand site >> banner « -20% on Mature skin products » K P I S O L U T I O N S Conversion Satisfaction client DMP Programmatique #1 Anticipate customer needs through personalization N.B: use cases are purely illustrative C O N V E R T
  7. 7. 8 D ATA A C T I VAT I O N Segment « prospect | mature skin » identified on Brand site >> banner « -20% on Mature skin products » K P I S O L U T I O N S Conversion Customer satisfaction DMP Perso #1 Anticipate customer needs through personalization N.B: use cases are purely illustrative C O N V E R T
  8. 8. 9 #2 Propose a relevant offer for a Customer with clear needs D E V E L O P N.B: use cases are purely illustrative D ATA C O L L E C T I O N 1st party data Alrealdy Customer « Home insurance » 2nd party data Visit on a comparative Insurance site Segment: « Intentionist | Auto insurance » enrichment
  9. 9. 10 #2 Propose a relevant offer for a Customer with clear needs N.B: use cases are purely illustrative D ATA A C T I VAT I O N Segment « Intentionist | Auto insurance » identified on Brand site >> chat box and NBA K P I S O L U T I O N S DMP CRM Churn Customer value Customer Satisfaction D E V E L O P 1. Inbound call The Customer is calling for a question about the last received invoice 2. Real time decisioning Based on Customer history, the best offer is proposed in real time 3. Next Best Action After having answered the initial request, the agent is proposing the best offer (Auto insurance)
  10. 10. 11 … and a performance that follows the consumers adoption TEST EVOLUTION A/B/n & MVT Testing Segmentation & Targeting Personalization Objective JOURNEY OPTIMISATION IDENTIFICATION & TARGETTING OF KEY SEGMENTS PERSONALIZATION FOR EACH VISITOR IN REAL TIME Results Conversion rate optimisation for the ENTIRE audience +2-6% Conversion rate optimisation for 30% of the audience +5-10% Granularity
  11. 11. 12 ... But how to ensure a UX coherence with omnichannel?
  12. 12. 13 For an omnichannel experience, organization silos must collapse Connected Boutique / IoT Web / Mobile / App Pub Social Legacy Ex: Data Management Platform & CRM onboarding Ex: Social CRM Ex: Testing & PersonalizationEx: Attribution modeling Web / Mobile / App Social Legacy Pub Boutique connecté / IoT Ex: PoS Analytics Customer value From a silo-ed approach… … to an omnichannel approach Organization & Data
  13. 13. 14 5 pillars for a (truly) omnichannel personalization UX SOLUTION ECOSYSTEM DATA ORGANIZATION & GOVERNANCE INTELLIGENCE
  14. 14. 15 Moving from a Channel-centric to a Customer- centric organisation Multi-channel Channel-centric Customer-centric Omnichannel OFFERS OFFERS SERVICES Offer push on various channels with synchonization Real time inbound and outbound Marketing based on Customers needs and behaviours PUSH OUTBOUNDINBOUND ORGANIZATION & GOVERNANCE
  15. 15. 16 An Agile Toolbox for scoping and management PERSONAE From customers to real life personae A Persona represents a person in real life, being part of a target group. That enables to discuss about real experiences and pain points, with human beings EXPERIENCE MAP Identifier les points clés du parcours client By persona, the experience map provides an overview of the touchpoints and interactions (digital + offline). This shows clearly improvement areas and overlap MVP Prioritie User Stories with a customer centric approach The key features are defined and prioritized for each step of the customer journey by project. The selection will then define the MVP itself with the first items to build and deliver. PROTOTYPES Build quick and concrete value propositions During the scoping exercise, the prototype enable to deliver some first features and interactions to test and experiment. Visual prototypes enable a quick decision making process, and improve TTM UX
  16. 16. 17 « Design by Data » approach for improving UX 4 Business insight Behavior analysis AB testing Web, app, email … optimisation 2 31 Data Analyst UX expert Expert AB Data Analyst Dev + 139% usage Identify Pain points Define Testing campaigns and optimize resources Define best options and versionsValue driven analysis Product Owner Product Owner Product Owner WHO?IllustrationsTOOLS UX Digital analytics DMP Digital analytics AB Testing Session replay Voice of the User Digital Analytics Wireframing
  17. 17. 18 An acceleration of available data from various channels (digital & offline) EARNED PAID OWNED e-mail twitter partners bill complaint retail RSS survey profile apps options history account phone facebook flickr bebo sharethis yahoo blogger clics press RTB trade-show SEM mobile TV media SEO website, mobile website, Apps, Blog, e-commerce Adwords, display, retargeting, social, ADV Media coverage, Digital PR, virality page view DATA
  18. 18. 19 Data Marketing maturity model: omnichannel & real time Marketing as a target Customer experience maturity Implementation complexity Personalized journeys Omnichannel & Real time Marketing Customer centricChannel centric User centric advertising (Programmatic) Omni- channel Marketing platform Centralized ad serving Digital media attribution modelling Media & CRM Centric DMP Analytics & TMS Next Best Action (NBA) Dynamic Creative Optim (DCO) Analytical CRM 360° DMP Testing & Personalization Social CRM Data Lake IT ECOSYSTEM
  19. 19. 20 A simple architecture from data to activation Collect & Analyse Target Activate Inidividual & anonymous data Audience & segments targetting (static & dynamic) Users and customers activation in omnichannel mode SEM RTB Offline Online Conversion IT ECOSYSTEM DO NOT FOCUS ONLY ON 3RD PARTY
  20. 20. 21 But numerous apps for targetting & activating… Target Activate Online Offline CRM Media / RTB Social ads Web / Mobile TV / Print Mailing In / Outbound calls Point of Sales e-mail Push / SMS COMMERCIAL PRESSURE DCO User-centric advertising Search Owned Social DMP (media & CRM centric) DMP Social CRM Testing / Perso App Conversion Omnichannel Marketing ADVERTISING PRESSURE NBA (Next Best Action) Earned Media VARIOUS APPLICATIONS & RULES IT ECOSYSTEM
  21. 21. 22 Data Marketing solutions with various objectives CRM SFA DCO DMP (media & CRM centric) DMP Social CRM Testing / Perso Omnichannel Marketing Next Best Action (NBA) Chatbots360° Customer analytics Customer central repository IT ECOSYSTEM
  22. 22. 23 GDPR impact: challenge or opportunity? Editors need to facilitate these new requirements ... and brands need to check the entire data chain (up to the data providers) GDPR – start date May 2018 Right to be forgotten Omnichannel consent Data portability Right to know when data has been hacked Privacy by design Fine up to 4% of turnover DATA GOVERNANCE USER EXPERIENCE IT ARCHITECTURE DATA IMPACTS
  23. 23. 24 Lost with Data Marketing ecosystem?
  24. 24. 25 The Digital Benchmark as a first and quick answer http://www.thedigitalbenchmark.com/
  25. 25. 26 The Digital Benchmark | categories Ad Verification & Brand Safety Ad-Server Affiliate Management Demand Side Platform (DSP) Display Dynamic Creative Optimization (DCO) Retargeting Sell Side Platform (SSP) Sponsored Content Trading Desk ADTECH Account Based Marketing (ABM) Clients' review & Scoring Emailing Feed Management Marketing Automation Personalization (web, email) MARKETING App Store Optimization In-Store Marketing Mobile App Analysis Mobile App Builder Mobile Engagement Mobile Platforms MOBILE MARKETING A/B Testing Delivery Order Management Payment Product Information Management (PIM) Product Recommendation Push notification Subscription Management ECOMMERCE OPTIMIZATION Ecommerce Marketing Automation Engagement & Loyalty Phygital Web-to-Store CONNECTED COMMERCE SOCIAL MEDIA Brand Reputation Influencer Relationship Management (IRM) Social Media Intelligence Social Media Management User Generated Content (UGC) Contact Management Customer Engagement Customer Experience Customer Relationship Management (CRM) Customer Service Document Management Landing Pages Lead Management Product Catalog Proposal Management Quotes Referral Tracking Social CRM Survey Management CRM Attribution Marketing Data Management Platform (DMP) Data Onboarding Web Analytics DATA MGT & INSIGHTS Data Governance Data Network Management Data Sources Dataviz Machine Intelligence Market Intelligence Semantics DATA SCIENCE Identity and Access Management (IAM) Performance Monitoring Search Engine Optimization (SEO) Tag management Usability TestingWEBSITE & APP OPTIMIZATION Blogging Content Management System (CMS) eCommerce Platform Marketplace Platform WEBSITE & APP CREATION Collaboration Project Management Workflow Management Workplace DIGITAL WORKING AVANT GARDE Blockchain Bot Builder Platform IoT Cloud Platform
  26. 26. 27 Return on experience
  27. 27. 28 Key learnings when building your ecosystem Mobile Media / Channel Attribution Unicity Cross-device journey > Test mobile journeys, envisage a dedicated mobile Marketing ecosystem > Analyse all interactions with channels and media via consolidating journeys to define attribution models (engagement, conversion) > Identify individuals within the journeys, and ensure the unicity of the activation, and envisage a central Customer repository > Identify cross-device usage to improve targeting on these journeys Agility > Propose an agile approach to set up and activate use cases, and facilitate “test & learn” Data quality & governance > Ensure that a truly data governance is in place to share cross-domain data, and improve quality
  28. 28. 29 #AI (Artificial Intelligence): some clear expectations, but some clear gaps in omnichannel mode Deep Learning on fans behaviours Chatbots (truly conversational) Testing & Perso Fingerprinting Look alike modelling EVOLUTION Face and emotion recognition a hyper-specialisation that does not improve the omnichannel dialogue coherence
  29. 29. 30 Embark Business prioritires, the organization, archietcture constriantes in order to define a target ecosystem LEGAL (!! GDPR) DATA COLLECTION & OWNERSHIP IT ARCHITECTURE PROCESSES & GOVERNANCE USE CASE TEST & LEARN
  30. 30. 31 QUESTIONS?
  31. 31. 32 digitbench18WIFI digitbench18 # CONTACT JEAN MENEVEAU Partner meneveau@colombus-consulting.com +33 6 50 73 60 99
  32. 32. 33 # THANK YOU FOR YOUR ATTENTION

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