5/2/2017 1

Creating Customer Identities . Driving Marketing ROI

Use of AI to future proof your marketing

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Experience 1: Targeting the Wrong Audience

Traditional retargeting methodologies which operate with limited non-contextual data.

Experience 2: Using the Wrong Channel to market

Broadcasting a generic message to all customers - ignored by most.

Experience 3: Irrelevant ContentOffers, coupons that are irrelevant /

meaningless.

Consumers experience bad marketing everyday

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Reason 1: I will hound you if I can contact you

Reason 2: Everyone is the same to me, nameless & faceless

Reason 3: Because I don't know you, I will spray and pray

…. and Brands lose over $500 billion* as a result!

Marketing methods employed by Brands are the root cause!

* 48% of all digital marketing spend is wasted today as per Nielsen’s Digital Ad Ratings Service

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The $1.2 trillion Marketing Industry does not have to be a blind game of chance!

0.8%

1.1%

4%

3%

Avg. Fb Ads CTR

Avg. Google Ads CTR

Avg. Email Open Rates

Avg. Email CTR

Negligible conversions from Social Impressions to Trxns

Unsustainable campaign ROI caused by:Wrong Audience selectionWrong Content choicesWrong Channel Choices for marketingWrong time of campaignsLack of identify leads to lack of personalisation

Marketers today engage the same consumer differently due to lack of unified identify=> leading to ridiculously low performance of most marketing campaigns

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The crowded tools market is adding fuel to this massive fire!

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And it shows no signs of slowing down

The average enterprise deploys ~ 91 tools to manage their marketing

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Social

Mob App

Paid Media

Webinars

BTL Campaigns / D2C

Web CMS

SEO

Website & Mobile Analytics

Ux / Landing Pages

Location / Personalisation

CRM

Marketing Automation

Tools

Enrichment

DW / DL

Retargeting Tools

Notifications

Email / SMS

Customer Support

Cloud Telephony

Live Chat

Internal Communication

Customer Feedback

Checkout Cart

Web Analytics & Attribution

Business Analytics

Channel / Partner Transaction Systems

POS

ERP

And the typical enterprise marketing stack is complex

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❖Complex Stack: Typical enterprises have anywhere between 20 & 50 channels & tools

❖Offline transition data is rarely leveraged: Digital stack is already very complex, Offline Data Sources / Transaction

measurement and tracking increases complexity drastically.

❖Data resides in Silos: None of the individual tools/channels talk to each other. So, multiple Data Silos exist.

❖No system consumer level identity: Impossible to build “primary key” based mapping for data from various independent

sources. Lack of single identity means no leverage of comprehensive customer interaction information at the enterprise

level to deliver meaningful conversations & campaigns

❖Channel focus instead of consumer focus: Each node delivers independent consumer experience focused just on that

channel or tool’s history;

Challenges with the typical enterprise marketing stack

<Typical Stack Depiction in following slide>

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Social

Mob App

Paid Media

Webinars

BTL Campaigns / D2C

Web CMS

SEO

Website & Mobile Analytics

Ux / Landing Pages

Location / Personalisation

CRM / ERPMarketing

Automation Tools

Enrichment

DW / DL

Retargeting Tools

Notifications

Email / SMS

Customer Support / Chat

Cloud Telephony

Internal Communication

Customer FeedbackCheckout Cart

Web Analytics & Attribution

Business Analytics

Channel / Partner Transaction Systems

POS

1. FirstHive Integrates the disjointed Enterprise MarTech StackImmediate Impact of FirstHive

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FirstHive’s Unification algorithm unlocks invaluable data & insights on consumer behaviour

2. FirstHive’s ML Unification Engine builds a Universal Consumer FirstHive ID

Continuously enriched, Unique Cross-channel Consumer Identity

FirstHive ID

✓ Probabilistic ML algorithms that build unique consumer identities

✓ Maps anonymous interactions, transactions & behaviours to identified consumers

✓ Real time Identity building

✓ Every incremental campaign enriches identities & behaviour tags

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Patent Pending real-time UniquificationTM algorithm

Supervised Learning Technique under Machine Learning for Classification

Algorithm.

Fuzzification Clustering algorithm to partition data sets, using 27 parameters &

counting

UniquificationTM Algorithm based on positive

probability distribution

Factoring in Negative probability impact on the UniquificationTM process

UUID – Universally unique identifier, a 128-bit

‘FirstHive identity’ for each customer

Our Secret Sauce: FirstHive’s Advanced ML Consumer Identity building Algos

How FirstHive builds unified system level consumer identities

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FirstHive sets the enterprise on a high performance marketing roadmap

3. FirstHive’s AI Recommendation Engine Optimises Marketing Choices

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The proof of the pudding ….. you know the rest

Acquire Engage Retain Drive Advocacy

Acquire Banking Major in India

Drove over a million new referrals

from individual consumers’ mail

and Facebook graph

Indonesia - Lifestyle major

Relevant nudges and content

delivered via chat bots to

shoppers subject to content

already viewed and source

Beauty major

Co opted salon partners for

PoS integration and overlay

with sampling data and

provide relevant nudge via

key influencers

Boosted a QSR apps’

lead funnel by over 7X

by providing access to

the pseudonymous

profiles

5/2/2017 15

The Future of Marketing is Glorious with

Thank You

Vishal Sukhejavishal@firsthive.com

(M) 77188 08076