Elevator Pitch & Soundbites
Chris Zakharoff · SSE
I take powerful technology platforms and make them work for real businesses by understanding them well enough to close the gap between what they can do and what an organization actually needs.
Through-Line

20 Years, Same Problem

  • I've spent 20 years at this intersection, understanding complex technology deeply enough to make it real for enterprise buyers.
  • I started building personalization infrastructure manually at Adobe, and Ensighten before CDPs existed, ran strategic SE at Cloudinary for nearly 7 years, and was the GTM R&D engine at Copy.ai building custom AI solution products for customers during period of 480% revenue growth.
  • The thread: technical discovery, POC delivery, and translating capability into outcomes that move deals and retain customers.
AI Angle

Built Toward This

  • I was prototyping manually a decade ago what AI agents now do natively, behavioral signals, content affinities, intent thresholds, next-best-offer logic.
  • My R&D team and I earned a patent building the early infrastructure for this problem at Ensighten in 2015.
  • I've been building toward this moment for 20 years, and I want to be in the room where that capability meets enterprise buyers who need someone to make it real.
Translation Pitch

Both Sides of the Room

  • I can sit with a CTO and a CMO simultaneously and speak fluently to both without switching modes.
  • The technical depth is real, I've built production systems, earned a patent, and written the code.
  • So is the business case translation. That gap is what most SEs struggle with, and it's what I've built a career on.
Builder Pitch

I've Built Versions of This

  • I built a custom AI translation package for Microsoft, a post-sales intelligence system from scratch, and a full production agentic content engine on Vercel AI SDK.
  • I built a tag management system in 2007, three years before the first commercial TMS hit the market.
  • I built a 1st party anonymous behavioral contextualization framework as a calculated metrics based concierge before AI.
  • I understand what I'm selling because I've built versions of it myself, and that changes every conversation.
Story Bank
BUILD

Ensighten: Context Layer

personalization depth · AI origin story · builder credibility · through-line
S
Martech tools had no unified behavioral context, just fragmented signals
T
Build the missing layer that makes personalization actually work
A
Designed Calculated Context Layer, behavior, attributes, timing into one story. Intent thresholds, next-best-offer logic.
R
US Patent 9,553,918. Foundation for what AI agents now do natively.
WINBUILD

EMBARQ: 408% Sales Lift

quantified outcome · optimization credibility · building from nothing
S
Flagship internet product underperforming. No geo-targeted offer logic.
T
Drive measurable sales lift through optimization
A
MVT and A/B via Omniture. Geo-targeted intelligent offers. Built custom in-house TMS in 2007.
R
408% increase in high-speed internet sales.
BUILDSCALE

GTM Engine: From the Ground Up

building from scratch · CS architecture · agentic systems · startup SE
S
20 enterprise customers. No playbooks, no lifecycle infrastructure, no inherited anything.
T
Stand up the entire Solutions function
A
Built customer lifecycle engine end to end, onboarding, health scoring, VoC signals, renewal motions, agentic content engine on Vercel AI SDK.
R
Closed-loop CS system with persistent account intelligence across every renewal cycle.
SCALE

Cloudinary: SE to Manager

leadership · enterprise SE craft · ROI framing · team building
S
Principal SE on strategic accounts, company scaling fast
T
Step into management without dropping IC performance
A
Promoted to SE Team Manager while maintaining full strategic account load. Hired and ramped new SEs. Built offsite training program.
R
Founding member of Strategic Accounts. Company grew $20M → $100M ARR during tenure.
SCALE

Symantec: Center of Excellence

scaling expertise · enablement · enterprise org complexity
S
80+ optimization-engaged personnel at Symantec, no unified framework
T
Build a center of excellence that scales without me in every room
A
Built documentation, tools, training resources. Strategic consulting across the org.
R
150+ optimization tests per month running globally.
BUILD

Ensighten London: Never Again

failure · preparation · self-awareness · what you do differently now
S
One week into Ensighten. Sent to present to senior partners in London. Back half of slides built by someone else, no context handed to me.
T
Deliver a credible presentation to a room of experienced professionals on week one of the job
A
Crushed the first half, material I owned. The back half fell apart. Felt the weight of that room full of posh professionals.
R
Vowed never to be in that position again. Have over-prepared for everything I produce ever since. I make my material my own even when inheriting someone else's.
SCALE

Cloudinary: Trained My Replacement

coaching · leadership · knowledge transfer · what success looks like
S
Leaving Cloudinary Strategic Accounts, one of the most tenured SE roles on the team
T
Ensure the seat didn't collapse behind me
A
Hired someone with a media background, mentored him through full ramp, transferred institutional knowledge of strategic accounts until he could operate independently.
R
He's still there and still excelling. The measure isn't that I did the job well, it's that the function survived and grew after I left.
SCALEPOLITICS

Cloudinary: Restructured My Promotion

influencing leadership · pushing back · good judgment · changing someone's mind
S
Offered SE Manager promotion for the Americas. Accepting as structured would have pulled me out of IC strategic account work entirely and hurt team number.
T
Find a way to say yes to leadership intent without compromising performance for anyone
A
Pushed back on the structure, not the offer. Proposed splitting Americas into East and West, promoted the most capable SE to co-manager alongside me. Made the case that split attention would hurt accounts, team, and company.
R
Leadership agreed. We ran the team together. I handed him full control on the way out, transition was nearly seamless because the infrastructure was already in place.
DEALWINBUILD

Microsoft: Translation Package

discovery · POC delivery · enterprise presales · AI fluency
S
Microsoft came in for standard marketing use cases
T
Run discovery, scope the real engagement
A
Pulled on global deployment thread, uncovered 40-language translation need. Built 7-language AI package with polyglot prompt engineer. Iterated to 99% accuracy, 95% legibility.
R
Expanded scope of paid pilot. All original use cases also delivered.
DEALWIN

Etsy: UGC Video

net new enterprise · technical complexity · scale architecture · inbound
S
Etsy came in inbound to enter video for the first time, UGC at marketplace scale, millions of seller-uploaded videos needing transformation, delivery, and performance
T
Qualify the inbound, scope the full technical architecture, close net new enterprise
A
Designed end-to-end solution: transformation at upload, performance optimization, scale handling, and dual CDN delivery for UGC video at millions-of-files scale.
R
Million-dollar-plus contract. Been live ever since.
DEALWINEXPAND

Nintendo: Land and Expand

complex account strategy · land and expand · creative SE leadership
S
Nintendo approached us for full DAM. Their historic offline archive meant we couldn't meet the full need.
T
Find the right entry point rather than force a bad fit
A
Pivoted to WebDAM for ecommerce as the wedge. Led cross-SE brainstorm, went onsite, developed custom use cases for their world. Expanded from WebDAM to image optimization to video over one year.
R
Roughly half a million dollar contract over one year.
DEALDISPLACEEXPAND

Tesla: Rip and Replace

competitive displacement · land and expand · engineering champion · incumbent
S
Tesla running legacy DAM and media delivery, outdated, less featured. Internal engineering champion saw what we could do.
T
Replace the incumbent and expand across the entire property
A
No bake-off needed. Engineer ran his own proof, saw the results vs TRON, made the call. Started with key pages, expanded to ecomm media, homepage, then all pages. Fully API-driven.
R
Full rip and replace of a major brand's entire media infrastructure. Contract roughly half a million, expanding from there.
DEALWINEXPAND

Mattel: Consolidation and Transformation

enterprise transformation · incumbent replacement · multi-stakeholder · expansion
S
Mattel consolidating 200+ brand sites into a unified platform, replacing Scene7 and kicking out AEM. AE had prior relationship with VP Ecomm IT from his Nordstrom days.
T
Win the media, transformation, and delivery layer of a massive platform consolidation
A
They handled architecture, we owned all media, transformations, dynamic delivery, enterprise multi-CDN. Spoke to what the VP cared about: performance, dynamic media on flagship product, consolidation, direct-to-consumer data ownership.
R
Landed low-to-mid six figures, kept expanding with renewals. Relationship kept growing.
DEALLOSSRECOVERY

Airbnb: Lost and Won Back

deal that went south · relationship persistence · personalization at scale · recovery
S
During COVID, Airbnb explored AI video summarization for host experience packages. Tech wasn't fully there and UGC scale made it cost-prohibitive. They built in-house.
T
Stay relevant and keep the relationship alive without a live deal
A
Stayed persistent. Maintained the relationship through the down period. Following year: Airbnb Travel Stamps, dynamically compiled personalized location badge cards for guest profiles at scale.
R
Annualized contract that renewed. A lost deal became a long-term relationship by staying in the room without forcing it.
DEALLOSSBUILD

Gap: Lost at the Line

deal that went south · competitive loss · pricing strategy · what you'd do differently
S
Gap needed a complex media transformation engine in a marketer-friendly GUI, integrated with Amplience.
T
Win on technical merits and close
A
Built a custom Amplience integration, a genuine technical differentiator. Made the case, got to out-for-signature.
R
Lost last minute to a competitor at a fraction of the price. They compared our full solution price to a competitor's minor component price. Apples to Oranges. Would price more modularly from the start.
MY SE APPROACH
Discovery

How I Find the Real Problem

  • Start with connection: rapport first, clear agenda, diagnosis before pitch.
  • Make pain safe to admit: frame the problem as common, not embarrassing. “We work with a lot of customers who struggle with X, that’s not an issue for you, is it?” lowers defensiveness and lets the buyer admit pain without pressure.
  • Pull the real thread: the first stated problem is rarely the full problem. Keep following the operational, technical, and business consequences until the real issue appears.
  • Quantify the cost: tie the current state to time, revenue, risk, customer experience, internal effort, or missed opportunity.
  • Use their words back: mirror the buyer’s language so the solution feels anchored in their reality, not my script.
  • Prescribe instead of pitch: map the recommendation to the problem they surfaced, not to a generic feature tour.
  • Scope the smallest credible proof: define the POC or next step around the shortest path to proving real value in their environment.
Demo

How I Make the Product Real

  • Lead with the outcome: what changes for the customer matters more than what the feature is called.
  • Make it relevant fast: use their use case, their language, and their operating model wherever possible.
  • Build toward the aha moment: focus the demo around the moment that makes the buyer see the future state clearly.
  • Show restraint: avoid showing everything. Good demos are edited, not exhaustive.
  • Pause after impact: give the room time to absorb the point before moving to the next capability.
  • Handle technical objections live: answer directly, draw the architecture, expose tradeoffs, and avoid hand-waving.
  • End on the business case: bring the conversation back to outcomes, cost of inaction, and why the change matters now.
  • Draw clear boundaries: credibility comes from knowing where the product is strong, where it is not, and how to say both plainly.
Objections

How I Work Through Pushback

“We already have a solution”
Start with the current workflow. What still routes to humans? What still breaks? What still takes too long? The gap usually shows up in the edge cases.
“AI will replace our agents”
Acknowledge the concern first. Then separate expert work from repetitive work. The best framing is augmentation: giving the team more leverage, not erasing the team.
“Security / data privacy”
Ask for the specific requirement before answering broadly. SOC 2, HIPAA, GDPR, retention, residency, PII, and access controls all require different conversations.
“AI is not accurate enough”
Treat accuracy as a testable claim. Define the threshold, run the proof in their environment, and show where controls, review loops, and evaluation fit.
“Timing is not right”
Look for the condition behind the delay. What would have to be true for the timing to become right? That usually reveals the real blocker.
“Too expensive”
Shift from price to cost of inaction: current effort, delay, missed revenue, customer impact, operational waste, or risk exposure.