Section 01
Start Here
Use this as the Packsize ramp path. It starts with Context Center because Apollo AI needs Packsize-specific positioning before it can write or research well.
Julius and Jose wanted a concrete walkthrough, a training library, and a workflow Nick can build with Packsize's own account-fit criteria. This hub gives the team the first working version.
What Packsize should define
Target industries, shipping signals, fulfillment triggers, core personas, disqualifiers, and examples of accounts the team knows are a strong fit.
What Apollo will run
AI Research fields for account fit, contact fit, call scripts, and workflow routing once the first criteria set is approved.
What reps should review
First-run AI outputs, sequence messages, call task notes, and any account where the AI score conflicts with rep judgment.
Configure Apollo AI Context Center
Add Packsize's offering, ICP, value points, objections, and preferred call to action. This improves AI Research, messaging, and sequence creation.
Create the account fit field
Start with Bronze, Silver, Gold, Platinum. Gold and Platinum accounts become the first outreach priority.
Add contact fit and call script fields
Rank the person, then generate persona-aware call notes reps can read before dialing.
Attach the workflow to intent or web visits
When a target account shows intent, Apollo scores it, finds relevant contacts, scores those contacts, and queues reviewed outreach.
Section 02
Context Center Setup
Context Center is the foundation. It tells Apollo AI what Packsize sells, who it helps, and how to write without sounding generic.
Minimum fields to complete
Company overview, offering, value proposition, customer pain points, product differentiators, primary competitors, and default call to action.
Recommended guardrail
For the first week, reps should preview every AI-written message before sending. After a good sample set, Packsize can lower the review threshold.
Company name: Packsize Offering: Packsize helps companies that ship physical products create right-sized, on-demand packaging using packaging automation, software, and equipment. The goal is to reduce box inventory, cut DIM weight costs, lower void fill, improve packing throughput, and reduce packaging waste. Ideal customer profile: Companies with meaningful fulfillment, distribution, e-commerce, manufacturing, or logistics operations. Strong-fit accounts often have high SKU variability, parcel shipping volume, multi-site warehouses, active fulfillment growth, automation initiatives, or sustainability commitments tied to packaging waste and shipping emissions. Primary buyers: VP or Director of Supply Chain, Operations, Logistics, Fulfillment, Warehouse, Distribution, Manufacturing, Continuous Improvement, Industrial Engineering, Procurement, and Sustainability. Customer pain points: - Too many standard box sizes and too much box inventory - High freight or DIM weight costs caused by oversized cartons - Manual packing decisions slowing down fulfillment teams - Excess void fill, corrugate waste, or sustainability pressure - Peak-season throughput constraints - Difficulty standardizing packaging across sites Value proposition: Packsize helps fulfillment and operations teams make the right box at the right time for each order. Customers can reduce corrugate use, lower shipping costs, improve packing consistency, free up warehouse space, and support sustainability goals. Product differentiators: - On-demand right-sized packaging instead of pre-made box inventory - Packaging automation paired with software - Fits high-mix fulfillment where order size and SKU dimensions vary - Supports cost, throughput, and sustainability outcomes Default call to action: Offer a 20-minute discussion to compare the prospect's current packaging flow against areas where right-sized automation may reduce waste, cost, or packing bottlenecks. Messaging style: Use direct, practical language. Avoid hype. Ask thoughtful questions about current fulfillment and packaging constraints. Make the message specific to the prospect's role and company evidence.
| Context Input | Why It Matters | Packsize Example |
|---|---|---|
| Offering | Gives AI the product category and operating model. | Right-sized, on-demand packaging automation. |
| Pain points | Guides outreach toward real operating friction. | DIM weight cost, corrugate waste, packing bottlenecks. |
| ICP | Helps AI judge fit and route the right accounts. | High SKU variability, parcel volume, warehouse footprint. |
| CTA | Keeps sequence endings consistent. | 20-minute packaging flow review. |
Section 03
AI Research Fields
These fields score accounts and contacts, then generate field-level outputs the team can filter, route, and reference in sequences.
Bronze
No clear physical product shipping or weak packaging fit.
Silver
Ships products, but limited evidence of scale or complexity.
Gold
Strong fulfillment footprint with automation, waste, or cost signals.
Platinum
High-volume, complex fulfillment with active growth or cost triggers.
Research {{account.name}} using {{account.website_url}} and available public web evidence.
Return one fit tier for Packsize: Bronze, Silver, Gold, or Platinum.
Score across these criteria:
1. Fulfillment and shipping volume
Look for distribution centers, warehouses, e-commerce shipping, parcel or freight operations, logistics pages, and warehouse job postings.
2. Packaging complexity and SKU variability
Look for diverse product sizes, mixed-cart e-commerce, industrial supply, consumer goods, automotive, electronics, furniture, or multi-category retail.
3. Warehouse automation and operational maturity
Look for automation, robotics, WMS, OMS, fulfillment modernization, logistics engineering, or supply chain transformation.
4. Sustainability and packaging waste pressure
Look for ESG goals, packaging reduction initiatives, carbon targets, recyclability, waste reduction, and Scope 3 shipping or packaging commitments.
5. Cost pressure and trigger events
Look for new fulfillment centers, e-commerce growth, logistics expansion, ERP or WMS upgrades, peak-season hiring, or supply chain leadership changes.
Scoring logic:
Bronze = no clear physical product shipping or low fulfillment complexity
Silver = ships products, limited evidence of scale or packaging complexity
Gold = strong fulfillment footprint with SKU variability, sustainability, cost, or automation signals
Platinum = high-volume shipping, complex fulfillment, automation maturity, and active growth or cost-reduction triggers
Output only one word:
Bronze, Silver, Gold, or Platinum
You are an AI sales analyst working for Packsize.
Evaluate {{contact.first_name}} {{contact.last_name}}, {{contact.title}}, at {{account.name}} as a potential buyer or influencer for Packsize.
Use only fields that are present. If a field is empty, ignore it.
Available context:
Contact name: {{contact.first_name}} {{contact.last_name}}
Title: {{contact.title}}
Department: {{contact.department}}
Seniority: {{contact.seniority}}
Company: {{account.name}}
Industry: {{account.primary_industry}}
Company size: {{account.number_of_employees}}
Company description: {{account.description}}
Technologies: {{account.technologies}}
Revenue: {{account.revenue}}
Account fit tier: {{account.Packsize Fit Score}}
Scoring:
5 = Excellent. Supply chain, logistics, warehouse, fulfillment, manufacturing, procurement, operations, or sustainability role with strong company fit.
4 = Strong. Role is adjacent to operations or transformation, and the company shows fulfillment, cost, automation, or sustainability signals.
3 = Moderate. Some operations connection, but limited influence or limited evidence of shipping complexity.
2 = Weak. Low connection to fulfillment or packaging decisions.
1 = Poor. No clear connection to physical shipping, packaging, warehouse, fulfillment, or sustainability decisions.
Output format:
Packsize Contact Fit Score: X/5
Readiness Level: High, Medium, or Low
Why this person is a fit:
- [3 bullets based only on available data]
Top use cases for this persona:
- [3 Packsize-relevant use cases]
Likely objections:
- [3 likely objections]
Suggested messaging angle:
[One practical line]
Call opener:
[1 to 2 sentences]
Email opener:
[1 to 2 sentences]
Generate a short cold-call script for {{sender_first_name}} from Packsize to use with {{contact.first_name}}, {{contact.title}}, at {{account.name}}.
Use the account fit tier and contact fit score to choose one relevant reason for the call:
Account fit tier: {{account.Packsize Fit Score}}
Contact fit score: {{contact.Packsize Contact Fit Score}}
Routing logic:
Use Automation and Throughput mode when the account fit tier is Gold or Platinum, or when the title includes Operations, Warehouse, Fulfillment, Distribution, Logistics, Supply Chain, Continuous Improvement, Industrial Engineering, or Manufacturing.
Use Sustainability and Cost Reduction mode for Sustainability, Procurement, Finance-adjacent cost owners, or lower-fit accounts.
Rules:
- 75 to 100 words
- Natural, direct, and easy to read before a dial
- Do not mention the fit score or routing logic
- Reference one evidence-based trigger if available
- End with a soft question
Output format:
Opener:
[1 to 2 sentences]
Relevance hook:
[Tie one trigger to their role]
Value bridge:
[How Packsize may help reduce waste, cost, labor, or packing bottlenecks]
Discovery questions:
- [Question tied to the role]
- [Question tied to the trigger]
Close:
[Soft ask for a 20-minute discussion]
Section 04
Intent and Web Visit Workflow
This is the workflow Julius asked about: a signal arrives, Apollo finds the right people, AI qualifies the account and contacts, then outreach queues for review.
Trigger fires
Start from Apollo Intent, Bombora or G2 intent, a web visit, or a saved search change. The target account becomes eligible for review.
Account fit score runs
Apollo AI Research returns Bronze, Silver, Gold, or Platinum. Gold and Platinum continue into high-priority routing.
Routing logic filters accounts
Gold and Platinum go to rep review. Silver can go to nurture. Bronze is suppressed until Packsize says otherwise.
Apollo finds the right contacts
Search for Supply Chain, Operations, Logistics, Fulfillment, Warehouse, Procurement, Sustainability, and related titles.
Contact fit and call script fields run
Reps get a ranked contact list plus call notes tied to the account signal and buyer persona.
Reviewed sequence enrollment
Enroll top contacts in the right sequence. Keep manual approval on until Packsize trusts the outputs.
High-touch track
Gold or Platinum account, 4 or 5 contact score, clear trigger. Use calls, email, and LinkedIn, with rep review before send.
Nurture track
Silver account, weaker trigger, or lower-fit contact. Use lower-volume education, light touches, and monitor for stronger buying signals.
Section 05
BDR Playbook
A rep-facing checklist for Julius, Jose, and new hires. Use this order for first-week training.
Search and list building
Start with title, department, seniority, industry, company size, and account tier. Save searches for repeatable work.
Waterfall enrichment
Run enrichment before sequencing so reps do not waste time on missing or stale contact data.
Sequences
Use mixed steps: email, call, LinkedIn, and manual tasks. Start with manual email review while the AI setup is new.
CRM sync
Confirm Salesforce field mappings and activity logging so Apollo work shows up where leadership expects it.
AI Research
Use custom fields for fit score, contact score, call script, and one-line personalization inputs.
Analytics
Review reply rate, booked meetings, call outcomes, step performance, bounces, and deliverability warnings.
| Day | Rep Action | Outcome |
|---|---|---|
| Day 1 | Connect mailbox, confirm profile, review Apollo navigation, open Context Center preview. | Rep can send, review, and understand where AI context comes from. |
| Day 2 | Build one saved people search for Supply Chain and Operations titles. | First target list is ready for enrichment and fit scoring. |
| Day 3 | Run account fit and contact fit fields on a small sample. | Team reviews outputs, corrects criteria, and approves the scoring logic. |
| Day 4 | Add top contacts to a reviewed sequence and inspect every generated message. | First Packsize outreach path is live with quality control. |
| Day 5 | Review analytics, replies, bounces, and call notes. Adjust prompts or sequence copy. | Week-one feedback becomes the next version of the workflow. |
Section 06
Prompt Library
Quick prompts reps can use in Apollo AI Assistant, ChatGPT, Claude, or internal prep notes. Each starts with Packsize context so the output is easier to apply.
Research [COMPANY NAME] for Packsize outreach. Packsize sells right-sized, on-demand packaging automation for companies that ship physical products. Tell me: 1. Do they appear to ship physical products at meaningful scale? 2. What evidence suggests packaging, fulfillment, shipping cost, or warehouse complexity? 3. Are there sustainability, waste reduction, or packaging commitments? 4. Are there hiring signals, facility news, or operational changes? 5. What are 3 talking points for a [TITLE] at this company? Keep the answer concise and cite the evidence source when possible.
Write a 3-sentence cold email from [YOUR NAME] at Packsize to [CONTACT NAME], [TITLE] at [COMPANY]. Context: Packsize helps companies create right-sized packaging on demand, reducing DIM weight costs, box inventory, packing bottlenecks, and packaging waste. Relevant signal: [INSERT SIGNAL] Rules: - Keep it plain and practical - Do not overstate claims - Make the first sentence specific to the signal - End with a soft question about whether it is worth comparing their current packaging flow against right-sized automation
Design a 6-step, 3-week Apollo sequence for Packsize targeting [TITLE / PERSONA] at [INDUSTRY] companies. Theme: [Automation efficiency / sustainability / cost reduction / packaging waste / fulfillment throughput] Requirements: - Mix email, call, LinkedIn, and manual review tasks - Keep each email under 100 words - Include a reason for the call task - Include one AI personalization variable suggestion per email - Assume manual review is on before sending Return: 1. Sequence structure by day 2. Subject lines 3. First sentence for each email 4. Call task notes 5. One improvement to test after week one
I am calling [TITLE] at [COMPANY] for Packsize. Likely objection: "[INSERT OBJECTION]" Packsize context: We help fulfillment, operations, and supply chain teams create right-sized packaging on demand to reduce shipping costs, corrugate waste, manual packing decisions, and box inventory. Give me: 1. A 2-sentence response that acknowledges the objection 2. A pivot to a Packsize value point 3. A question that keeps the conversation going 4. One thing not to say
Summarize this Packsize discovery call for CRM notes. Use these sections: 1. Company situation 2. Current fulfillment and packaging process 3. Pain points 4. Metrics, volume, sites, or systems mentioned 5. Decision criteria 6. Objections or risks 7. Agreed next steps Keep each section to 2 to 3 bullets. Do not invent missing details. [PASTE CALL NOTES OR TRANSCRIPT]
Section 07
Training Links
Official Apollo resources for the areas covered in the walkthrough. Start with Context Center, then AI Research, then sequences and workflows.
One week before the next session, Packsize should send Nick the workflow theme, 3 to 5 example target accounts, and 2 examples of good or bad AI output.