Downloaded 248 times
![Call Centre
Targeting
Campaign and
trigger emails are
personalised
based on
customer
behaviour
DMP
Analytics
Social Login
Web/Mobile
email
Tag Management
MVT
Behavioural data is collected via a tag
management system and fed into a
profiling DB for segmentation.
Personalised content is delivered to
the customer using an MVT tool
Display Ads
Social Media
Profiling DB stiches sessions
together across device and
channel and creates
segments
Customer profiles are
enriched with social data
which is linked via social
logins
Call centre agents use
profiling data to enrich their
conversations with
customers
User experience is tailored to
the campaign seen prior to
arrival
Customer experience is aligned
across channel and platform based
on information gathered about
them from any channel in real time
or near real time.
DATA LAYER
{
user: johnsmith,
id :123456,
agegroup : 18-25,
prevsearch: “NewYork”
“campaigns: [
123,
456,
334
]
}
The application
embeds customer
profile info in a
data layer on the
page](https://image.slidesharecdn.com/b1220alexlovelessv3-141112085532-conversion-gate01/85/WTF-is-a-Data-Strategy-WTF-Programmatic-UK-11-11-14-17-320.jpg)
Uploaded byDigiday
WTF is a Data Strategy? - WTF Programmatic UK, 11/11/14
A data strategy provides insights about customers to inform business goals across marketing channels. It creates a unified view of each customer by collecting data from websites, apps, purchases, and other sources to optimize their experiences. An effective data strategy uses analytics like machine learning and predictive modeling to segment customers and personalize interactions in real-time across channels.
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WTF is a Data Strategy? - WTF Programmatic UK, 11/11/14
- 1. WT F IS A DATA STRATEGY ? 1 1 T H N O V 2 0 1 4 Alex Loveless Head of Data Consulting @alexmloveless
- 2. Why the f**ka data strategy?
- 3.
- 4. What are yourbusiness’s short, medium and long term goals?
- 5. It’s all aboutthe customer Customers don’t experience channels PPC DISPLAY ORGANI C AFFILIAT ES EMAIL MOBILE WEB customer lifecycle JUST GIVE ME WHAT I WANT!
- 6. Data Insight BrandPlanning Omni-channel Planning Optimised Brand Experience
- 7. creates informs PPC SEO Email Social Web Mobile behaviour social 3rd party purchases CRM app analysis value prediction segmentation behaviour UX data media customer creative social
- 8. Time Horizon CustomerVolume Short Medium Long 1 customer ALL my customers Web/mobile analytics Data Lake/Single customer view Attribution Modeling Cross Channel Analysis DMP/Personalisation Ad Targeting/programatic Propensity Modeling Behavioural Segmentation Social Listening Social segmentation Customer clustering Propensity modeling
- 9. It’s cool man!Just use stuff you’ve, like, seen in the past to predict what might happen in the future, m’kay? Rev. Thomas Bayes Bayes’ Theorem
- 10. • Customer data • Purchase history • Social data Find data Look for clusters (segments) in the data Look for features in the segments Observe history of segments Create Bayesian training set Use to predict future states • Car lovers • Mums • Optimists • Gender • Demographics • Frequent purchases • Behaviours • Purchases • Loyalty • Likely next product • Likelihood to purchase in X days • Probable next destination • Pregnancy status • Likelihood to complain
- 11. CONTEXT Who arethey? Where are they? What are they doing? Who are they talking to? What devices are they using? How can we tailor their experience? What do they How are they feeling? want? Timing is everything! At home At work In a café On the move Eating Watching tv Social web Friends Family Colleag ues Laptop Tablet Phone Irritable Positive Stressed Excited To buy something To browse To compare prices Personaliz ed email Targeted content Deals Male/Fe male @some body 18 - 25 Optimised Experience
- 12. Sees Display ad Logs onto in-store network Searche s for “TV” Uses app from café Whatsap p link to friend Returns unwante d item Uses browser Bounces Social share Arrives from search Selects Uses app shoe size Multiple visit no purchase Opens email Complains Uses airport kiosk In store sale Social campaign
- 13. With more data resolution increases • Behaviour • 3rd party data • Browse habits • Singe device • Customer data • Email address/social profile • Geographic • Product affinities • App usage • Cross device
- 14. media CRM purchaseSocial DATA 2nd Party analytic s Offline Call Centre How do we do this in real time?
- 15. Data Management Platform(DMP) Clickstream/Conv. 3rd Party Data Data Exchange CRM/Customer PPC Call Centre Targeted Email/Comms Display Targeting Deals/Incentives Mailings/Inserts Online to Offline Offline/POS Web/Mobile Personalisation Social Events Call centre prequalification Loyalty programme segmentation Predictive analysis Data Inputs Outputs/Actions
- 16. OMNI-PPC CHANNEL PERSONALISED DISPLAY ORGANI C AFFILIATES EMAIL MOBILE WEB customer lifecycle EXPERIENCE
- 17. Call Centre Targeting Campaign and trigger emails are personalised based on customer behaviour DMP Analytics Social Login Web/Mobile email Tag Management MVT Behavioural data is collected via a tag management system and fed into a profiling DB for segmentation. Personalised content is delivered to the customer using an MVT tool Display Ads Social Media Profiling DB stiches sessions together across device and channel and creates segments Customer profiles are enriched with social data which is linked via social logins Call centre agents use profiling data to enrich their conversations with customers User experience is tailored to the campaign seen prior to arrival Customer experience is aligned across channel and platform based on information gathered about them from any channel in real time or near real time. DATA LAYER { user: johnsmith, id :123456, agegroup : 18-25, prevsearch: “NewYork” “campaigns: [ 123, 456, 334 ] } The application embeds customer profile info in a data layer on the page
- 18. DMP CRM Analysis Data Lake Customer Social Offline/ POS 2nd Party Logs Legacy Data Broker Call Centre 3 Other rd Party Data comes in from anywhere Data of all shapes and sizes live in the data lake Data data broker makes sense of data on the fly Do lots of cool stuff with the data 1 2 3 4
- 19. ANALYTICS DATA WAREHOUSE SINGLE CUSTOMER VIEW MASTER DATA MANAGEMENT BIG DATA BRAND EXPERIENCE OPTIMISATION
- 20. 1. Business strategyis key – what are your big questions? 2. It’s all about customer insight, more is better but any is great 3. Start big - go small
Editor's Notes
- #3 I’m assuming that, because you’re sitting here now you know the answer to this
- #4 Don’t have to rely on gut feel any more. Go find the answer. Reference “Black Swan” here
- #5 I want you to bear these in mind throughout this presentation
- #7 Channel agnostic, device agnostic, joined up, seamless, happy, pleasurable, and above all profitable. So how do we get to that point?
- #10 18th century Presbyterian minister who, perhaps ironically, showed how to use new evidence to update beliefs.
- #11 It’s not as hard as it sounds The trick is to operationalise it
- #13 I’ll take whatever I can get Accuracy is a secondary concern Don’t nneed to know everything just somethingf