[Mintigo Webinar] 5 Secrets To Closing More Deals Using Big Data Analytics

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To watch the entire webinar replay, please visit: http://www.mintigo.com/5-secrets-to-closing-more-deals-using-big-data-analytics/ Title: "5 Secrets To Closing More Deals Using Big Data Analytics" Description: Today’s B2B buyer doesn’t want to be sold…60% of them have already made a buying decision before they engage with a sales rep. But that doesn’t mean Sales should fall passive. If you want to break through the noise of a crowded market, you need the right information to initiate helpful conversations with ideal prospects. Your secret weapon – Big Data Analytics. Join us to hear how Mintigo’s SVP of Sales Swayne Hill and his team doubled their rate of pipeline production by leveraging new types of data publicly available on the social web to get into good conversations with the right people. You’ll learn how Big Data will help you: - Focus on the right accounts - Find the best contacts - Figure out what interests them - Create a relevant, personalized approach - Engage all buyer roles through the sales cycle If you work in Sales Management or Sales Operations, you won’t want to miss this practical wisdom culled from decades of quota-busting experience. About The Speaker: Swayne Hill, Senior VP of Sales at Mintigo Before coming to Mintigo, Swayne spent years building high-performing Sales teams at Cloud9 Analytics, a leading Sales Forecasting and Business Intelligence solution provider, and Cognos, where he helped the company grow from $50M to almost $1B in revenue and was acquired by IBM. He sits on several high-tech advisory boards and holds a Bachelors degree in economics from University of Toronto. Swayne sits on several high-tech advisory boards and holds a Bachelors degree in economics from the University of Toronto. He also writes the blog “Data Driven Sales Management”.

Business Technology

Secrets
To
Closing
More

Deals
Using
Big
Data

Analy6cs

Swayne
Hill,
SVP
Sales

Min0go

5
Ways
We
Use
Big
Data

1. 
2. 
3. 
4. 
5. 

Priori0ze
Accounts
(+25%)

Find
the
best
contacts
(2X)

Learn
their
interests
(+40%)

Create
a
personalized
approach
(3X)

Engage
all
buyer
roles
in
the
sales
cycle
(+20%)

Priori6ze
Accounts

We
used
to…

•  Assign
territories
and
priori0ze

leads
based
on
state,
city,

company
size
and
industry

Problem

•  Arbitrary
coverage

•  Missed
opportunity

•  Demo0vated
AE’s

Using
Big
Data
Analy6cs

…we
generated
a

more
precise

deﬁni0on
of
our

total
addressable

market
(TAM)

Invested
in

Marke0ng

Automa0on

Early

Technology

Adopters

Business-‐to-‐
Business

High
PPC

Spenders

Priori6ze
Accounts

Now
we…

•  Align
territories
based
on

the
true
distribu0on
of
TAM

•  Priori0ze
and
route
leads

based
on
TAM
ﬁt

•  Get
op0mal
coverage
on

the
best
opportunites

Find
The
Best
Contacts

We
used
to…

•  Buy
‘000’s
of
contacts
from

D&B,
OneSource,
InfoGroup,

Data.com
and
the
like

Problem

•  Stale
contact
details

•  Poor
targe0ng
value

•  Waste
of
0me
for
AE’s

Your
Favorite
List
Broker

SELECT
*

FROM
“Contacts”

WHERE
“JobTitle”
=
‘VP’

OR
“JobTitle”
=
‘CIO’

ORDER
BY
“State”

Using
Big
Data
Analy6cs

…we
found
signals

indica0ng
who
is

more
likely
to

engage

VP

Find
The
Best
Contacts

Now
we
look
for
things
like…

•  Smiling
faces
(3.8x
more)

•  New
on
the
Job
(2.5x
more)

•  Socially
ac0ve
(2x
more
likely)

And
avoid…

•  VP
job-‐level
(9x
less)

✔

✔

✔

VP

✖

Learn
Their
Interests

We
used
to…

•  Seek
out
research
analysts

•  Go
to
conference
keynotes

•  Educate
ourselves
on

industry
trends

Problem

•  Disconnected
from
reality

Using
Big
Data
Analy6cs

...we
scan
social

networks
looking

for
paeerns
in
our

TAM
that
reveal

poten0al
interests

Learn
Their
Interests

Now
we
know…

•  Who
they
follow
and
what

they
share
on
Twieer

•  Which
groups
they’re

aﬃliated
with
on
LinkedIn

•  What
technologies
they
use

and
projects
that
may
be

emerging
for
them

Personalized
Approach

We
used
to…

•  Batch,
blast
email
and
dial
for
dollars

•  Figure
we’d
make
up
for
quality
on

volume

Problem

•  Missed
opportunity
to
make
a

sincere
connec0on

•  Burned
out
our
market

Using
Big
Data
Analy6cs

…
we
translate
interests
into
personaliza0on

What
we’re
selling!

Relevant!

What
interests
them!

Personalized
Approach

No
we…

•  Insert
intelligence
into
our

intro
messaging

•  Do
it
at
scale
using

Salesforce
variable

replacements
and
HTML

templates

•  Get
3x
higher
connec0on

rates

Engage
All
Buyers

We
used
to…

•  Travel
for
face-‐to-‐face
mee0ngs

•  Buy
lunches

•  Play
golf

Problem

•  Too
expensive
and
makes

an
AE
single-‐threaded

Using
Big
Data

…we
enrich

accounts
with
more

contacts
and

automa0cally

segment
them
into

buyer
roles

Engage
All
Buyers

Now
we…

•  Nurture
contacts
all
around

our
entry
point
with
relevant

messaging
and
content

•  Warm
up
the
decision-‐group

even
before
they
get
pulled

into
the
process

•  Eased
a
single-‐point-‐of-‐failure

Send
ROI

problem
for
AE’s

stories

Invite
to
Best

Prac0ce
Webinars

Send
Analyst

Research
Reports

Big
Data
Analy6cs
=
Sell
More

1. 
2. 
3. 
4. 
5. 

Priori0ze
Accounts
(+25%)

Find
the
best
contacts
(2X)

Learn
their
interests
(+40%)

Create
a
personalized
approach
(3X)

Engage
all
buyer
roles
in
the
sales
cycle
(+20%)

Min6go
Can
Help

Take
the
next
step…

•  Check
out
www.min0go.com

•  Register
for
a
product
demonstra0on

•  Talk
to
one
of
our
experts

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TO WATCH THE RECORDING OF THIS WEBINAR, GO TO: http://www.mintigo.com/how-docusign-built-a-world-class-lead-nurturing-program/ In 2012, DocuSign doubled its pipeline and far exceeded its sales targets. The company achieved these results because of the commitment and partnership of its marketing and sales team, led by VP of Demand Generation Meagen Eisenberg, to build out a world class lead nurturing and demand generation program. With over a dozen personas to target, 80,000 engaged leads to process each quarter, and more than 50 different nurture tracks, the DocuSign team is clearly doing something right. Hear the secrets behind the success of DocuSign’s lead nurturing program in this must-attend webinar. Both marketing automation novices and veterans will walk away from this session amazed and inspired by the best practices for accelerating your leads through the funnel. In this webinar, you will learn how to: - Focus on the right Personas based on interests - Create a lead scoring system that works - Map content according to Persona interests, buying stage & lead score - Measure success & optimize Guest Speaker: Meagen Eisenberg VP of Demand Generation at DocuSign Meagen has spent over 18 years in high-tech. In 2012 she received the SuperNova Award in Matrix Commerce and in 2011 the Marketing Visionary Markie award within the marketing automation field. Before joining DocuSign, she was Director of WW Demand Generation at ArcSight, an HP Company, and prior to that she led worldwide programs and events at TRIRIGA (acquired by IBM) for integrated workplace management systems. She has an MBA from Yale School of Management, and a Bachelor of Science degree in MIS with a minor in CSC from Cal Poly – San Luis Obispo. About Mintigo The Mintigo marketing intelligence platform continuously searches the big data of the web and social profiles to help marketers find and engage their best prospects. Mintigo analyzes the needs and interests of 30 million B2B prospects, so marketers and sales reps can engage each prospect with the right message and product. Companies like Box, BMC, Cloudera, DocuSign, and Edmunds use Mintigo to get more clicks, more shares, and more pipeline. To learn more follow @mintigo and visit www.mintigo.com.

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Navigating the seed funding landscape can be complex and demanding. Thanks to insights from Steve Schlafman of RRE Ventures, their detailed presentation sheds light on this critical phase of startup development. Key Points from the Presentation: 1) Sources of Seed Capital: Explore diverse funding sources from venture capital to angel investors and learn how to leverage them effectively. 2) Preparing for the Pitch: Understanding what investors look for in a seed stage startup is crucial— from traction and product to team dynamics. 3) The Pitch Itself: Learn how to create FOMO (Fear of Missing Out) among investors and how to convey your startup's value compellingly. 4) Post-Pitch Strategy: Discover what steps to take after your pitch to maintain momentum and secure funding.

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[Mintigo Webinar] 5 Secrets To Closing More Deals Using Big Data Analytics

1. Secrets To Closing More Deals Using Big Data Analy6cs Swayne Hill, SVP Sales Min0go

2. 5 Ways We Use Big Data 1.  2.  3.  4.  5.  Priori0ze Accounts (+25%) Find the best contacts (2X) Learn their interests (+40%) Create a personalized approach (3X) Engage all buyer roles in the sales cycle (+20%)

3. Priori6ze Accounts We used to… •  Assign territories and priori0ze leads based on state, city, company size and industry Problem •  Arbitrary coverage •  Missed opportunity •  Demo0vated AE’s

4. Using Big Data Analy6cs …we generated a more precise deﬁni0on of our total addressable market (TAM) Invested in Marke0ng Automa0on Early Technology Adopters Business-‐to-‐ Business High PPC Spenders

5. TAM Size & Elements

6. Priori6ze Accounts Now we… •  Align territories based on the true distribu0on of TAM •  Priori0ze and route leads based on TAM ﬁt •  Get op0mal coverage on the best opportunites

7. Find The Best Contacts We used to… •  Buy ‘000’s of contacts from D&B, OneSource, InfoGroup, Data.com and the like Problem •  Stale contact details •  Poor targe0ng value •  Waste of 0me for AE’s Your Favorite List Broker SELECT * FROM “Contacts” WHERE “JobTitle” = ‘VP’ OR “JobTitle” = ‘CIO’ ORDER BY “State”

8. Using Big Data Analy6cs …we found signals indica0ng who is more likely to engage VP

9. We Learn More Every Day

10. Find The Best Contacts Now we look for things like… •  Smiling faces (3.8x more) •  New on the Job (2.5x more) •  Socially ac0ve (2x more likely) And avoid… •  VP job-‐level (9x less) ✔ ✔ ✔ VP ✖

11. Learn Their Interests We used to… •  Seek out research analysts •  Go to conference keynotes •  Educate ourselves on industry trends Problem •  Disconnected from reality

12. Using Big Data Analy6cs ...we scan social networks looking for paeerns in our TAM that reveal poten0al interests

13. Looking for Likely Interests

14. Learn Their Interests Now we know… •  Who they follow and what they share on Twieer •  Which groups they’re aﬃliated with on LinkedIn •  What technologies they use and projects that may be emerging for them

15. Personalized Approach We used to… •  Batch, blast email and dial for dollars •  Figure we’d make up for quality on volume Problem •  Missed opportunity to make a sincere connec0on •  Burned out our market

16. Using Big Data Analy6cs … we translate interests into personaliza0on What we’re selling! Relevant! What interests them!

17. Personalized Approach No we… •  Insert intelligence into our intro messaging •  Do it at scale using Salesforce variable replacements and HTML templates •  Get 3x higher connec0on rates

18. Engage All Buyers We used to… •  Travel for face-‐to-‐face mee0ngs •  Buy lunches •  Play golf Problem •  Too expensive and makes an AE single-‐threaded

19. Using Big Data …we enrich accounts with more contacts and automa0cally segment them into buyer roles

20. Upload More Contacts

21. They’re Routed to Personas

22. Sent For Nurture

23. Engage All Buyers Now we… •  Nurture contacts all around our entry point with relevant messaging and content •  Warm up the decision-‐group even before they get pulled into the process •  Eased a single-‐point-‐of-‐failure Send ROI problem for AE’s stories Invite to Best Prac0ce Webinars Send Analyst Research Reports

24. Big Data Analy6cs = Sell More 1.  2.  3.  4.  5.  Priori0ze Accounts (+25%) Find the best contacts (2X) Learn their interests (+40%) Create a personalized approach (3X) Engage all buyer roles in the sales cycle (+20%)

25. Min6go Can Help Take the next step… •  Check out www.min0go.com •  Register for a product demonstra0on •  Talk to one of our experts

26. Secrets To Closing More Deals Using Big Data Analy6cs Swayne Hill, SVP Sales Min0go

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