Demand Generation
Building demand generation programs that create and nurture pipeline — from multi-channel campaigns through ABM (Account-Based Marketing), content syndication, and pipeline reporting.
When to Use
- Filling the top of the funnel with qualified leads
- Running integrated multi-channel demand campaigns
- Implementing ABM for target accounts
- Measuring pipeline influence and attribution
- Scaling demand generation efforts
Demand Gen Channels
DEMAND_CHANNELS = {
'content': 'Blogs, whitepapers, eBooks, research reports',
'webinars': 'Live and on-demand educational sessions',
'paid': 'Search, social, display, retargeting',
'email': 'Nurture sequences, newsletters, campaigns',
'events': 'Conferences, trade shows, user groups',
'ABM': 'Targeted account campaigns, 1:1 and 1:few',
'partners': 'Co-marketing, channel partners, affiliates',
'direct': 'Outbound sequences, cold outreach',
}
def demand_mix(budget: float, channels: List[str]) -> Dict:
"""Recommend demand generation budget allocation."""
recommended = {}
if len(channels) <= 2:
recommended = {c: budget / len(channels) for c in channels}
else:
recommended[channels[0]] = budget * 0.35
remaining = budget * 0.65
for c in channels[1:]:
recommended[c] = remaining / (len(channels) - 1)
return recommended
Common Pitfalls
- Spray and pray — blasting the same message to everyone ignores segmentation
- Vanity metrics — impressions and clicks don't equal pipeline
- No attribution — can't tell which channel drives SQLs and revenue
- Ignoring existing pipeline — demand gen fills top, but existing pipeline needs nurturing too
- Content not aligned — TOFU content doesn't lead to BOFU conversion paths
Verification Checklist
- Channel mix defined with budget allocation
- Content mapped to buyer's journey stages
- Attribution model (first-touch, multi-touch, or custom)
- Pipeline reporting (MQLs → SQLs → Opportunities → Revenue)
- ABM target account list defined
- Nurture sequences for unconverted leads