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The Use of A.I. in Pipeline Build - A Case Study
“How to make pipeline build more effective by
embedding analytical practices in sales.”
Or
“If you join the gym, you can’t escape having to
lift a few weights every now and then.”
Barry Magee
Director of Business Intelligence
Citrix Sales & Marketing EMEA
“Busy Being Busy” : what’s the real pipeline PROBLEM?
Visible Problem : dips in channel pipeline to business mean we need to drive more self-
generated pipeline internally. This applies sales and marketing alike, all teams – field and
digital sales covering all market segments from SMB right up to Enterprise accounts.
Root Causes : busy being busy - the current mechanisms for building pipeline are not effectively structured….
A rain of lists No direction Return on Time
No feedback
2 3 4
Poor Data
1 5
3%
97%
“AI” : what was the intended SOLUTION?
Proposed Solution : build an embedded data-driven process that provides a system to
optimise sales effort. It should allow managers and sellers see where market potential exists
and help them prioritise account and territory management to optimise pipeline build.
Customer SELECTION
• WHICH client should I engage next?
• WHAT Sales Play or Reason of Call?
• WHO should I engage within Client
• HOW do I get more information?
Create!
new AI “layer”
Customer RESEARCH
• WHERE is the equipment installed?
• WHICH contracts are in place?
• WHICH multi-vendor equipment?
• WHAT’s the latest contract/asset status?
Enhance!
business as usual
“Organisational Machine Learning” : what was the PROCESS?
Proposed Solution : build an embedded data-driven process that provides a system to
optimise sales effort. It should allow managers and sellers see where market potential exists
and help them prioritise account and territory management to optimise pipeline build.
Organisational
“Machine Learning”
“Elephants” - what were/are the CHALLENGES?
Anticipated Challenges : there is both a technical and operational – business transformation
dimension to tackle. This is not a ‘tool’ we’re building but a new way of working, prioritizing
effort and driving execution. It’s 20% technical and 80% people & process related.
Technical People & Process
1. Getting Data: need to both
enrich existing accounts and
acquire new “TAM” data.
2. Account Ownership: there
was poor hygiene on who
owned which account.
3. Use-Cases: multiple
approaches to pipeline build –
license expand, opportunity
expand, leverage buying
signals, telemarking campaign.
4. Lack of Strategic Coherence:
differing management views
of what was ‘best’ sales
tactic.
5. Is this my job?: pipeline build
not formally part of role – only
dedicated BDRs paid on pipe.
6. Traction/Distraction: there
are many competing initiative
vying for seller attention.
7. Manager Adoption: sellers
will only engage if their
managers are driving agenda.
8. Cadence Process: cadence
focusses on forecast of existing
pipe – not building new pipe.
9. GTM conflict: can cause
conflict if channel lose out on
opportunity “identification”
margin from transactions.
“More Productive Effort” : what were the RESULTS?
Leading Indicators : we need to target two key factors – A) the conversion rate from
engagement to opportunity (==targeting) and B) the volume of client engagements we are
driving. The two combined will yield higher pipeline.
• 3% external industry
benchmark.
• 10% is average over
time with dips in periods
between ‘Blitz’ weeks
• Average within ‘Blitz’
focus weeks approx. 13%
• Competing activities
on seller time – other
initiatives
• Lack of cadence –
each manager needs
to embed into weekly
reviews
10%
3%
5
0
Conversion Rate
Concluded Weekly Engagements /Seller
Win Rate: Equal to BAU performance Sales Velocity: 30% shorter sales cycle Oppty Values: Equal to BAU performance
“More Informed Decisions” : what are the IMPROVEMENTS?
Core Capabilities : we now have a single centralised workflow process which optimizes
pipeline build effort for whichever team (sales, marketing, business development) adopts
and embeds it into their way of working.
Am I talking to the right PERSON at the
right ORGANISATION?
Who
do I call next?
What do we KNOW about client and
what’s the right TOPIC to lead with?
What
do I talk about?
Where do I get TIME TO CALL and
when is best to ENGAGE?
When
do I call?
How do I provide my customer with
RIGHT INFO the RIGHT WAY
How
should I engage?
Which is BEST SALES RESOURCE to
use for client set?
Which
resource do I use?
1 2 3 4 5
Adoption Programme Critical
Executive Sponsorship Day 1
3
Managers Lead Culture
2
1
Products vs Solutions
4
Edison for
Sales
Edison for
Marketing
Edison for
Planning
The Use of A.I. in Sales & Marketing Pipeline Build - A Case Study

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The Use of A.I. in Sales & Marketing Pipeline Build - A Case Study

  • 1. The Use of A.I. in Pipeline Build - A Case Study “How to make pipeline build more effective by embedding analytical practices in sales.” Or “If you join the gym, you can’t escape having to lift a few weights every now and then.” Barry Magee Director of Business Intelligence Citrix Sales & Marketing EMEA
  • 2. “Busy Being Busy” : what’s the real pipeline PROBLEM? Visible Problem : dips in channel pipeline to business mean we need to drive more self- generated pipeline internally. This applies sales and marketing alike, all teams – field and digital sales covering all market segments from SMB right up to Enterprise accounts. Root Causes : busy being busy - the current mechanisms for building pipeline are not effectively structured…. A rain of lists No direction Return on Time No feedback 2 3 4 Poor Data 1 5 3% 97%
  • 3. “AI” : what was the intended SOLUTION? Proposed Solution : build an embedded data-driven process that provides a system to optimise sales effort. It should allow managers and sellers see where market potential exists and help them prioritise account and territory management to optimise pipeline build. Customer SELECTION • WHICH client should I engage next? • WHAT Sales Play or Reason of Call? • WHO should I engage within Client • HOW do I get more information? Create! new AI “layer” Customer RESEARCH • WHERE is the equipment installed? • WHICH contracts are in place? • WHICH multi-vendor equipment? • WHAT’s the latest contract/asset status? Enhance! business as usual
  • 4. “Organisational Machine Learning” : what was the PROCESS? Proposed Solution : build an embedded data-driven process that provides a system to optimise sales effort. It should allow managers and sellers see where market potential exists and help them prioritise account and territory management to optimise pipeline build. Organisational “Machine Learning”
  • 5.
  • 6. “Elephants” - what were/are the CHALLENGES? Anticipated Challenges : there is both a technical and operational – business transformation dimension to tackle. This is not a ‘tool’ we’re building but a new way of working, prioritizing effort and driving execution. It’s 20% technical and 80% people & process related. Technical People & Process 1. Getting Data: need to both enrich existing accounts and acquire new “TAM” data. 2. Account Ownership: there was poor hygiene on who owned which account. 3. Use-Cases: multiple approaches to pipeline build – license expand, opportunity expand, leverage buying signals, telemarking campaign. 4. Lack of Strategic Coherence: differing management views of what was ‘best’ sales tactic. 5. Is this my job?: pipeline build not formally part of role – only dedicated BDRs paid on pipe. 6. Traction/Distraction: there are many competing initiative vying for seller attention. 7. Manager Adoption: sellers will only engage if their managers are driving agenda. 8. Cadence Process: cadence focusses on forecast of existing pipe – not building new pipe. 9. GTM conflict: can cause conflict if channel lose out on opportunity “identification” margin from transactions.
  • 7. “More Productive Effort” : what were the RESULTS? Leading Indicators : we need to target two key factors – A) the conversion rate from engagement to opportunity (==targeting) and B) the volume of client engagements we are driving. The two combined will yield higher pipeline. • 3% external industry benchmark. • 10% is average over time with dips in periods between ‘Blitz’ weeks • Average within ‘Blitz’ focus weeks approx. 13% • Competing activities on seller time – other initiatives • Lack of cadence – each manager needs to embed into weekly reviews 10% 3% 5 0 Conversion Rate Concluded Weekly Engagements /Seller Win Rate: Equal to BAU performance Sales Velocity: 30% shorter sales cycle Oppty Values: Equal to BAU performance
  • 8. “More Informed Decisions” : what are the IMPROVEMENTS? Core Capabilities : we now have a single centralised workflow process which optimizes pipeline build effort for whichever team (sales, marketing, business development) adopts and embeds it into their way of working. Am I talking to the right PERSON at the right ORGANISATION? Who do I call next? What do we KNOW about client and what’s the right TOPIC to lead with? What do I talk about? Where do I get TIME TO CALL and when is best to ENGAGE? When do I call? How do I provide my customer with RIGHT INFO the RIGHT WAY How should I engage? Which is BEST SALES RESOURCE to use for client set? Which resource do I use? 1 2 3 4 5 Adoption Programme Critical Executive Sponsorship Day 1 3 Managers Lead Culture 2 1 Products vs Solutions 4 Edison for Sales Edison for Marketing Edison for Planning