Scott shows us the technical side of lead gen through segmenting leads and ranking them in your system before reaching out. What you will learn: -Internal tools to build for lead segmenting. -How to teach this to your salespeople. -How to focus on the right leads. -Juice all areas of your pipeline. Visit SalesHacker.com for more sales hacks, tips, and tactics.

1. UNIFIED BOOKING & DISTRIBUTION PLATFORM
FOR BUSINESSES PROVIDING ACTIVITIES

2. PROBLEM
NICHE
FRAGMENTED
SMB’s
Narrower focus on niche,
geography, or vertical
Fragmented markets often lack
organized data
More challenging to identify and
reach

3. Pre-Qualification
Hyper PreQualification
can double your
success

4. NEW PROBLEM
Marketing guy needs to filter100 specific scenarios around
data
Marketing guy walks over to engineer and begins to verbalize
the 100 specific scenarios around filtering data from database
Do the math on time and salaries

5. SQL String Builder
 = PreQual()
pq
pq.filterCitiesLoose([‘city1’, ‘city2’, ‘city3’]) # String value – Filters cities by loose
match
pq.filterCityLoose('Tahoe') # String value
pq.filterCityPrecise('Tahoe') # String value (city name)
pq.filterState('NV') # String value (State abbreviation - XX)
pq.filterKeyWord('kayak') # String value
pq.filterKeyWords(['farm', 'farmstay', 'hotel']) # Array. Exaple: ['item1', 'item2',
'item3']
pq.filterRank(15) # Integer

6. Example
pq.filterState('FL’)
pq.excludeCities(['Key West', 'Miami', 'Naples', 'Saint
Augustine', 'Fort Lauderdale', 'Destin', 'Miami Beach',
'Orlando', 'Marathon'])
pq.filterKeyWords(['jet boat', 'sailing', 'motor boat', 'yacht'])
pq.filterOutKeyWords(['museum', 'convention', 'library',
'market', 'zoo', 'gallery', 'gardens', 'performing arts', 'state
park', 'monument', 'stadium', 'arena', 'chamber of commerce',
'nature center', 'visitors center', 'visitor center', 'church',
'shop', 'shops', 'outlets', 'country club', 'college', 'mall', 'falls',
'recreation', 'national forest', 'nursery', 'historic site', 'historic
park', 'comedy club', 'farm’])

7. Output SQL String

SELECT company, url, contact, email, phone, city, state, postal_code, country, rating, rankplace FROM usa_customers
WHERE id>0 AND ((company NOT LIKE '%museum%' AND title NOT LIKE '%museum%') AND (company NOT LIKE
'%convention%' AND title NOT LIKE '%convention%') AND (company NOT LIKE '%library%' AND title NOT LIKE
'%library%') AND (company NOT LIKE '%market%' AND title NOT LIKE '%market%') AND (company NOT LIKE '%zoo%'
AND title NOT LIKE '%zoo%') AND (company NOT LIKE '%gallery%' AND title NOT LIKE '%gallery%') AND (company NOT
LIKE '%gardens%' AND title NOT LIKE '%gardens%') AND (company NOT LIKE '%performing arts%' AND title NOT LIKE
'%performing arts%') AND (company NOT LIKE '%state park%' AND title NOT LIKE '%state park%') AND (company NOT
LIKE '%monument%' AND title NOT LIKE '%monument%') AND (company NOT LIKE '%stadium%' AND title NOT LIKE
'%stadium%') AND (company NOT LIKE '%arena%' AND title NOT LIKE '%arena%') AND (company NOT LIKE '%chamber
of commerce%' AND title NOT LIKE '%chamber of commerce%') AND (company NOT LIKE '%nature center%' AND title
NOT LIKE '%nature center%') AND (company NOT LIKE '%visitors center%' AND title NOT LIKE '%visitors center%') AND
(company NOT LIKE '%visitor center%' AND title NOT LIKE '%visitor center%') AND (company NOT LIKE '%church%' AND
title NOT LIKE '%church%') AND (company NOT LIKE '%shop%' AND title NOT LIKE '%shop%') AND (company NOT LIKE
'%shops%' AND title NOT LIKE '%shops%') AND (company NOT LIKE '%outlets%' AND title NOT LIKE '%outlets%') AND
(company NOT LIKE '%country club%' AND title NOT LIKE '%country club%') AND (company NOT LIKE '%college%' AND
title NOT LIKE '%college%') AND (company NOT LIKE '%mall%' AND title NOT LIKE '%mall%') AND (company NOT LIKE
'%falls%' AND title NOT LIKE '%falls%') AND (company NOT LIKE '%recreation%' AND title NOT LIKE '%recreation%')
AND (company NOT LIKE '%national forest%' AND title NOT LIKE '%national forest%') AND (company NOT LIKE
'%nursery%' AND title NOT LIKE '%nursery%') AND (company NOT LIKE '%historic site%' AND title NOT LIKE '%historic
site%') AND (company NOT LIKE '%historic park%' AND title NOT LIKE '%historic park%') AND (company NOT LIKE
'%comedy club%' AND title NOT LIKE '%comedy club%') AND (company NOT LIKE '%farm%' AND title NOT LIKE
'%farm%') AND (company NOT LIKE '%institute%' AND title NOT LIKE '%institute%') AND (company NOT LIKE '%store%'
AND title NOT LIKE '%store%') AND (company NOT LIKE '%memorial%' AND title NOT LIKE '%memorial%') AND
(company NOT LIKE '%spa%' AND title NOT LIKE '%spa%') AND (company NOT LIKE '%massage%' AND title NOT LIKE
'%massage%') AND (company NOT LIKE '%wellness%' AND title NOT LIKE '%wellness%') AND (company NOT LIKE
'%therapy%' AND title NOT LIKE '%therapy%') AND (company NOT LIKE '%golf%' AND title NOT LIKE '%golf%') AND
(company NOT LIKE '%links%' AND title NOT LIKE '%links%') AND (company NOT LIKE '%theater%' AND title NOT LIKE
'%theater%') AND (company NOT LIKE '%theatre%' AND title NOT LIKE '%theatre%')) AND (URL NOT LIKE
'%facebook.com%' AND URL NOT LIKE '%tripadvisor.com%' AND URL NOT LIKE '%yelp.com%' AND URL NOT LIKE
'%cox.net%') AND state = 'FL' AND (city NOT LIKE '%Key West%' AND city NOT LIKE '%Miami%' AND city NOT LIKE
'%Naples%' AND city NOT LIKE '%Saint Augustine%' AND city NOT LIKE '%Fort Lauderdale%' AND city NOT LIKE
'%Destin%' AND city NOT LIKE '%Miami Beach%' AND city NOT LIKE '%Orlando%' AND city NOT LIKE '%Marathon%')

8. COMPARISON
No Pre-Qualification
With Pre-Qualifiction
Open Rates: 48%
Open Rates: 48%
Engagement: 4.8%
Engagement: 9.5%

9. JUICE EACH PHASE OF FUNNEL