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Future of Research A 21st Century Romance

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A 21st century romance…

The connected consumer

‘Connected’ research

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2 Social

3 Data mixing

The 3 ‘technologies’ driving the future of research

1 Mobile

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Accuracy Granularity Prediction

Speed Data & Marketing Integration

ROI

Providing 6 key benefits that make research relevant in a connected world

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1 Accuracy

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Accuracy: mobile gets us much closer ‘to the moment’ providing greater accuracy

1 17.6 10.6 14.0

2 7.1 9.1 9.2

3 34.6 30.0 45.9

4 3.8 24.2 0.1

5 1.7 2.5 2.1

6 7.0 9.5 10.7

7 1.2 2.8 0.9

8 1.6 2.4 1.3

9 0.7 1.8 0.5

10 24.7 7.1 15.4

Total 100 100 100

Industry share

Traditional survey

Mobile diary

Brands

What used in the past <time>? How much/how often/etc.?

‘In the moment’ record

Traditional Survey

0.49

Mobile Survey 0.88

R2

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Accuracy: And when we get closer to the moment, we can understand decision making much better

In reality few count at moment of purchase

Brand most important “in the moment” of purchase

Number of influences on purchase decision

Consumers make decisions quickly

3.8 influences mentioned per respondent

1.4 influences mentioned per purchase

The price Special offer

Well-known brand Drinks menu

Brand not available

Friends

Try something new

Complement food

Match the occasion

Drinks display

After the event Recruitment survey

In the moment mobile diary

Special offers, despite being a major tactical lever, are not cutting through.

0 20 40 60

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Accuracy: whilst social actually gives us a far more accurate and differentiated view on a brand’s positioning

0

0,1

0,2

0,3

0,4

0,5

0,6

Survey attribute

Social proxy

Brand 1 Brand 2

Correlation with changes in equity

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2 Granularity

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Granularity: getting closer to the moment helps us understand each potential selling ‘occasion’ with a far greater degree of granularity

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Granularity: and the context around occasions, as expressed in social, helps us understand these much better

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Granularity: whilst social lets us explode each occasion even further and identify consumer generated solutions

A mobile diary identifies a targetable moment

Sunday afternoon boredom N=150 cases

One Sunday afternoon of twitter data identifies many types of boredom across 28,000 tweets and discusses how to solve it

Movies Reading

Drawing

Snapchat

Homework Selfies

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3 Prediction

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1,71,81,92,02,12,22,32,4

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

2012 2013

4,05,06,07,08,09,0

10,011,012,013,0

Actual Predicted

Prediction: with the sheer volume of real-time data available, we can now create synthetic measures to model equity and sales

Automotive Brand

CPG – Short Purchase Cycle

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

2012 2013

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Prediction: and is typically predictive 2-4 weeks ahead of equity movements

Lead time to get the jump on competition

1 2 3 4 5 6 7 8 9 10 11 12

10 10

4 2

Modelled data from engaged ‘leading indicator’ group indicates your brand health will be “10” in X weeks.

2 3 4

Survey responses amongst mass market measure your brand health to be “10”.

6

The results of your survey based tracker tell you your brand health was “10” three weeks ago.

9

27

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4 Speed

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Speed: mobile drives brevity in survey design enabling automated solutions

week 1 week 2 week 3 week 4

24 hours 4 weeks

Definition Scripting and field

Data processing Modelling Deliverables Traditional concept

testing

Mobile concept testing

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Speed: with results in real-time, shifting the way we can manage our brands

Business gets real-time reports which highlight any unexpected changes

Consumer tells us each day what they eat/buy/see

Hello, you there? There’s a large uplift in buzz around Apple today

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5 Data & marketing integration

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Media audience Sales

ROI: data integration enables 1-to-1 targeting and measurement

Survey seed

Buy more

Buy the same

Buy less

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6 ROI

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Go to store

Consumer journeys can differ dramatically based on user profile

Buy offline

Milestone Online touchpoint Offline touchpoint

UK Low digital Total no. of touchpoints used: 3

Visit a store to narrow down selection

Post-purchase Discovering Planning Who Deciding

25-34 year old buying baby care

UK High digital Total no. of touchpoints used: 7

Buy online

Went to brand website to check product features and prices

Read expert reviews online to compare brands and narrow down selection

$

Spoke to friends and family

Found info in a brochure to get ideas and find out about brands

25-34 year old buying baby care

Search for information in store to make a faster decision

Spoke to friends / family to check find about good deals $

Searched for information in store

Spoke to store staff to compare brands and make faster decision

Found special offer, made final decision

Went to brand website

Wrote about the product on a social network

Used a search engine and wrote about the product on a review site

Check prices to make final decision

Spoke to friends and family

G1. Steps taken pre-purchase | G2. Touchpoints | G3. Needs met by touchpoints | G5. Post-purchase touchpoints Base: UK (2)

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We can then build specific journey profiles for each customer that can be used for customer engagement

Pre-store Occasion In store

56%

Relaxing at home

27%

With food at home

10%

Leisure out of home

Brand decisions made pre-store Brand decisions made in-store

73

Touchpoint interaction Mission Brands bought

29

46

21

Actively research the category

Saw some advertising

Did not research the category or see advertising

27

57

23

8

4

Weekly shop

Fill in

Meal

Specific trip

43

21

15

8

Brand X

Competitor

Competitor

Competitor

Bought on…

59 41

Full price Promotion

Go to

sto

re

Purc

hase

Shopper journey - Grocery %

23

Integrated thinking

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How does this all come together? Our vision is for a more flexible, iterative research architecture

Predictive spine Social and search

Slimmer survey Shorter, smarter surveys

Modular deep dives touchpoint evaluation, Qual etc.

Situational Equity Occasions

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A 21st century romance..!

‘Connected’ research

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