Lillian Pierson, P.E.
Chief Marketing Officer

I ♥
MARKETING

Lillian Pierson, P.E.

With nearly two decades in the industry, I've integrated my deep marketing expertise with a strong propensity for data and technology, thus establishing myself as a go-to strategist for launching state-of-the-art products and services across a wide variety of sectors.

My specialty is in developing unparalleled growth strategies and go-to-market plans that not only position brands at the forefront of their industries but also harness data insights, cutting-edge tech, and strategic innovation to drive substantial ROI and business growth.

The impact of my work is far-reaching: The products I've developed and launched have been used by approximately 2 million users worldwide, driving at least $6M in revenue for my clients. I've masterminded the launch of over 40 products globally. These products were tailored to resonate in diverse markets, with four different language adaptations thus far. From renowned corporations to agile startups, from the retail giants to the services sector, my strategies have been the backbone of their market outreach.

Notably, I've supported 10% of Fortune 100 companies, including 𝗔𝗺𝗮𝘇𝗼𝗻, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗗𝗲𝗹𝗹, 𝗜𝗻𝘁𝗲𝗹, 𝗪𝗮𝗹𝗺𝗮𝗿𝘁, and 𝗖𝗶𝘀𝗰𝗼.

My foundation doesn't just lie in my business acumen; I'm also entrenched in data and AI strategy, and have held a Professional Engineering license since 2014.

As a startup CMO, my mission is to bridge the gap between vision and execution, thus transforming product potential to market reality.

You can take a peek at my CV here.

If you'd like to discuss the possibility of me supporting your company & team, I'd love to chat with and can be easily reached you at Lillian@data-mania.com.

The client provided me with a limited amount of market research and interview data that they’d collected during the process of building the product. I did additional market research on SEMRush, Twitter, LinkedIn, and Product Hunt. 

 

Based on my analysis of their existing interview data, the market research, and the readily available product features, I identified that the best market for the product at that stage was the financial services industry.

Being a spreadsheet product, this product was of course up against spreadsheet behemoths, Excel and Google Sheets. Within that market, however, there was a significant trend wherein spreadsheet-based analysts are looking for more powerful, robust spreadsheeting capabilities than are offered by the traditional giants. 

This product promised to provide lightning-fast, powerful compute power within a spreadsheet environment so that spreadsheet analysts could analyze massive datasets without needing to learn SQL or Python or to move into a new analytical environment. 

Consequently, this product was well positioned to capitalize on that trend in demand. 

Competitor products included Equals and Rows.

The problem this product solved was Excel’s and Google Sheets’ inability to run complex calculations on massive datasets without freezing or crashing.

The largest market challenge we faced with this product was one of pricing and value proposition against the mainstream spreadsheet products, Excel and Google Sheets. Because Excel and Google Sheets are essentially free products, our unique value propositions – and the pain points that the product solved – needed to be substantial enough to justify charging for the product.

This challenge represented an opportunity for us to drive messaging and product differentiation such that it was focused almost exclusively on the product’s superior spreadsheet processing speed and its ability to analyze larger volumes of data than are possible within the free counterparts.

This differentiation also meant that we needed to target “spreadsheet superusers” exclusively – these were analysts who had enough frustration and pain around the slow spreadsheet problem and who were ready to spend money to have that problem solved.

“Spreadsheet superusers” is a nebulous term that needed refinement. 

Within our first round of experiments, I did a $1000 Google Ads test to test the following buyer segments: Avid Investors, Financial Services Professionals, Business Technology Enthusiasts, Business & Productivity Technology Software Users, Accounting Software Users, Business Financial Services Professionals.

With data generated via that ads test, and through extensive A/B testing, user surveys, and experimental optimizations, we were able to identify ideal segments for ads and to adjust the ideal customer personas to people who identified with at least one of the two following categories: 

(1) Financial Modeling Professionals 

(2) Spreadsheet Modeling Professionals

This was a complex SaaS product and we utilized 3 distinct campaigns to drive customers, users, and leads for the product. Those campaigns included:

  1. A live launch
  2. A simulated launch
  3. Ads traffic to an evergreen sales funnel

For brevity’s sake, I will summarize the buyer’s journey in aggregate below.

 

Awareness Mechanisms: 

  • Content Marketing: SEO blog posts & emails – Led a small team on an acquisition-focused website development project to develop a robust 55-page website (including conversion-optimized sales pages, a quiz funnel, surveys, and an SEO-optimized blog) and then drove an 85x increase in website visitors in 7 months

 

  • Social Media: Regular posts where our ideal customer persona is actively seeking solutions to their slow spreadsheet problem (ie; LinkedIn and Twitter)

 

  • Pay-Per-Click Advertising (PPC): Google Ads, Reddit Ads

 

  • Influencer Marketing: I proposed & initiated influencer marketing campaigns to drive product awareness. The larger part of the initiative was not pursued, but I was able to use my own influencer marketing channels to drive ~60 leads for the client.

 

  • Live Webinar and Webinar Replay

 

  • Referral Funnel: We successfully encouraged word-of-mouth referrals and got public testimonials.

 

  • Affiliate Marketing: (proposed & initiated, initiative canceled)



Consideration Mechanisms:

 

  • Product Demonstrations: Provided video showcases of the product in action directly on the sales page

 

  • Testimonials: I built a testimonials funnel that generated positive feedback from excited users.

 

  • Email Marketing: I led targeted email campaigns that provided deeper insights about the product and its benefits.

 

  • Retargeting Ads: I ran Google remarketing ads that targeted users who visited the website, to remind them of the product and decrease overall cost per acquisition (CPA).

 

  • FAQs: I built an FAQ bank for faster user support and then repurposed this content to overcome buyer objections in the FAQ section of the sales page.

 

  • Interactive Tools: I built a quiz funnel that helped prospects understand the value of the product while also generating market intelligence for our campaigns.

 

  • Community Engagement: Within my recommendations for a minimum marketable product, I suggested that we include an exclusive user community and weekly office-hours as a value-add to the product offer. We built out that community in Circle. 

 

Decision Mechanisms:

 

  • Free Trials: After some experimentation with pricing plans ($59.95/mo., $29.95/mo. & $1 trial), we settled on a free 30-day trial.

 

  • Promotions: We offered a limited-time 50% offer to drive sales during the simulated launch. We also offered exclusive grandfathered pricing to the first X number of customers who sign up.

 

  • Personalized Consultations: Within my recommendations for a minimum marketable product, I suggested that we include weekly group sessions and personalized concierge services to address any specific needs and concerns. We implemented this suggestion.

 

  • Live Chat Support: We offered real-time assistance to answer any last-minute questions or user support needs.

 

  • Guarantees: When charging for the product, we offered a 30-day money back guarantee.

 

  • Product Reviews:  I built a testimonials funnel that generated positive feedback from excited users. With permission, I added whichever testimonials I could to the sales page as social proof, to increase the conversion rate of the page.

 

  • Onboarding Materials: Within my recommendations for a minimum marketable product, I suggested that we offer a product academy that included video tutorials, pdf guides, and support call replays that make it easy for a customer to start using the product. I also suggested we include weekly live onboarding calls. We implemented these suggestions.

 

  • Exclusive Memberships: Within my recommendations for a minimum marketable product, I suggested that we include an exclusive user community and weekly office-hours as a value-add to the product offer. We built out that community in Circle. We implemented this suggestion. 



Touchpoints: Email, Sales Page, Live Chat, Google Ads, LinkedIn Page, Twitter Page, SEO-Optimized Blog, Live Launch Event

Pain Points: Slow, crash-prone spreadsheets that can’t meet the analytical processing demands of Spreadsheet Modeling Professionals

Motivations: 

  • Greater analytical efficiency and capability = Managerial happiness = Greater likelihood for promotion & raise
  • Less frustration at slow, crashing spreadsheets
  • Faster time-to-insight = Saves money

Data indicated that the “Spreadsheet Modeling Professionals” segment represented the largest opportunity in terms of revenue, market share, or strategic value – especially given the product resources and capabilities at that time.

 

Customer Journey Narrative

I wrote the following user narrative which we used on the sales page in order to connect with our ideal customer persona and convert them into paying customers.

“TO: All Spreadsheet Modeling Experts & Analysts Who Are Sick Of Dealing With Slow, Frozen, and Crashing Spreadsheets

Stop looking for new add-ins and formula best practices to try to solve your Excel spreadsheet problems. I have big, exciting news for you about the #1 thing you’re missing in your analytical toolset.

You were taught that spreadsheets should be powerful enough to execute any complex mathematical operation. Everyone’s using them after all… as advanced modeling tools, as databases, as personal finance trackers… Just load the data, add a header, and you’ll be good to go.

What went so wrong? 

Year after year, datasets got larger, and your manager’s expectations got higher. But the bigger that datasets got, the more problems you ran into with your spreadsheets.

They’re slow, they’re clunky… and frankly, most of them just crash and burn when you go to run a complex analysis across a large spreadsheet.

If you would’ve known that you’d spend so many of your waking hours building complex mathematical analyses in spreadsheets that simply can’t handle your data processing requirements, you probably would have thought twice about getting that math degree.

That’s exactly what almost every spreadsheet rockstar we’ve spoken to feels like, anyway.

No matter how many Add-Ins they’ve tried or formula best practices they put into place, the slow Excel spreadsheet problem could not be overcome.

God forbid they bring that data over to Google Sheets for some real-time collaboration with peers… That move almost always spelled disaster.

Sound familiar?

Maybe you’ve passed your busted Excel spreadsheets off to a programmer more times than you’d care to admit…

Maybe your company spent $10k+ on a custom-built application to crunch your data for you…

On certain days you may have wasted more time waiting on Microsoft Excel than you did with your own children…

We’ve all been annoyed by extremely misguided statistics, like:

“In Europe, advanced Excel users are wasting ~€55 billion every year by “misusing Excel”    – IDC UK

WE SAY: THAT STAT IS PURE RUBBISH

Maybe if advanced Excel users had spreadsheets powerful enough to do their jobs, none of that would be an issue.

Stop blaming analysts for spreadsheet limitations that they didn’t create!

If you’ve completely given up hope of ever using the full range of your hard-earned analytical expertise…

Please don’t feel bad.

It’s not your fault.

After enduring so many of these same spreadsheet frustrations myself, I almost gave up on the idea of using a spreadsheet to analyze large datasets or collaborate with peers.

 

A/B Testing (Messaging & Design)

After significant A/B Testing + experimental optimizations, I was able to identify ideal segments for ads and to provide data that justified adjusting the ideal customer persona from Financial Modeling Professionals to Spreadsheet Modeling Professionals.

 

Customer & User Feedback (Built-In & External Incentivized Surveys)

I built a testimonial funnel and quiz funnel which were both successful in generating useful user feedback. We also implemented a built-in product review module which was successful in generating a large list of 5-star user ratings for the product.

Pre-Launch Phase (4 Months)

REQUIREMENTS: Mission + Vision + Brand Values Articulation, Brand Story Formation, Market Research & Competitive Analysis, Define Minimum Marketable Product / Packaging / Pricing, Opt-In Freebie, Pre-Launch Website Setup, Sales Page Copy + Design, Community Setup, Email Setup + Welcome Sequence, Retargeting Ad Setup, Members Area Setup, Hiring, Team Management

Minimum Marketable Product:

Launch Phase (4 Months)

REQUIREMENTS: Channel Management, Team Management, Content Management, PPC Ads Management, Regular Nurture Content, Ads Creative, PPC Ads Set-Up

 

Weeks 1, 2, 3: Pre-Sale + Soft-Launch

The point of this launch is to get some customers and to build the bank of launch materials for reuse in the next launch. Warm-up advertising pixels. Execute pre-sale email launch to current email list.

 

EMAIL LAUNCH to current subscribers

  • Pre-Launch Email Sequence (goal: build know, like, trust factor, LinkedIn Page growth, build launch list)
  • Live Launch Event
  • Launch Email Sequence
  1. Free live masterclass (book on call to save 20%)
  2. Early-Bird Pricing (15% off)
  3. Early-Bird Pricing Ends (Urgency)
  4. Pricing goes to full price
  5. Last call emails (48 – 72 hours)

 

Weeks 4, 5, 6: Customer Onboarding + Delivery / Post-Launch Evaluation & Regrouping / Email List Nurture

  • Launch debriefing, team + partners celebrations, reformulate sales / launch plan for the next 2 quarters
  • Weekly nurture newsletter starts (to nurture all email subscribers)

 

Weeks 7, 8: Customer Onboarding + Delivery / Launch Regrouping / Nurture Audience

  • Heavy nurture email list, blog, social media

 

Weeks 9, 10: Simulated Launch

  • Ran a 2-week flash sale to test alternative price point and messaging

 

Weeks 11, 12, 13: Customer Onboarding + Delivery / Launch Regrouping / Nurture Audience

  • Heavy nurture email list, blog, social media

 

Weeks 14, 15, 16, 17, 18, 19: Live Launch To Warm Leads / Onboard Affiliates

  • Iterate on design, messaging, and pricing
  • Build evergreen sales funnel
  • Set-up ads and drive qualified traffic to the evergreen funnel
  • Finish building product growth levers for the “Acquisition, Activation, Retention, Revenue and Referral” funnel.

Unique Value Propositions

 
  • 100x faster spreadsheet performance, compared to Google Sheets
  • Backed by Bloomberg
  • The product has had a beta launch in July of 2022 and has received positive feedback.
  • The product promises deeper and more detailed insights compared to existing solutions like Excel or Google Sheets.
 

Messaging

  • Superior Performance: SheetRocks promises an enhanced spreadsheet experience, highlighting a “100x spreadsheet performance.” The implication is that it’s vastly superior to traditional spreadsheet tools.
 
  • Limited-Time Free Offer: By becoming a Founding Member now, users can access SheetRocks and its premium features for free during the beta phase. This emphasizes the value users will receive, especially given the monetary value attached to some of the features.
 
  • Urgency: There’s a recurring theme of urgency throughout the sales page. Users are reminded that the free access offer will retire after the beta phase, urging them to “lock down” their spot.
 
  • Unique Benefits: SheetRocks presents a range of features that are not commonly found in other spreadsheet platforms, such as over 400 built-in formulas, SOC 2 Compliance, and a fully programmable API.
 
  • Comparison to Competitors: SheetRocks positions itself as a superior alternative to existing spreadsheet solutions, specifically Excel and Google Sheets. It outperforms these platforms, as proven by the demo video provided on the sales page.
 
  • Comprehensive Support: The Planet SheetRocks White Glove Onboarding Program, along with the added bonuses, showcases a commitment to support and guide users. This includes concierge services, live onboarding calls, and more.
 
  • Positive Feedback: The sales page references early adopters’ positive reviews and testimonials to establish trust and reliability, suggesting that those who have already tried it are “in love” with the platform.
 
  • Call to Action: The sales page repeatedly urges visitors to become Founding Members, with clickable prompts like “YES! SAVE MY SEAT…” or “YES! SAVE ME A FREE SEAT…” designed to encourage sign-ups.

To facilitate risk analysis and contingency planning I always perform detailed alternatives analyses (via a multi-criteria decision-making matrix).

Before proposing a minimum viable product or launch strategy, I did a thorough evaluation of existing assets (ie; existing email list, interview data, and available product features). I followed that up with extensive market research and competitive analysis. 

I then defined 3 alternative, high-potential product-market-fit hypotheses. I did a complete multi-criteria analysis of these alternatives against 10+ mission-critical go-to-market criteria… and based on the weighted scores of the 3 alternatives, I suggested the minimum marketable product that we decided to launch. 

This minimum marketable product represented the lowest-risk, highest-reward alternative for bringing the product to market immediately.

  • Premium Pricing Strategy: Based on market research into the demographic and psychographic of the ideal customer persona, I suggested we price the product at $59.95/month for our initial test. This was to avoid devaluing the product and to test the market’s willingness to pay a higher price for it. The fact that we generated sales at this price not only drove revenue but also validated the hypothesis that there was a market for this product at this higher price point.

 

  • Discounting to Drive Sales & Data: We then experimented with a 50% off sale (via a simulated launch), aiming to both increase user numbers and gather more user data. This discount strategy was effective in increasing sales and user numbers.

 

  • Shifting to Evergreen Funnel & A/B Testing: To work towards validating product-market fit, I built an evergreen sales funnel and then drove ad traffic to two different offerings: a $1 trial and a free trial. The aim was to gather more user data and see which approach was more cost-effective in terms of user acquisition.

 

  • Results of the Test: A/B testing showed that the free trial attracted more users for a lower ad spend.  This resulted in 1,100 new users in the first month and provided us with the product usage data we needed to confirm whether product-fit was achievable.

 

Channels

  • Omni-Channel Marketing: 
    • Channels: Email, SEO-Optimized Blog, LinkedIn Page, Twitter, Google Ads
    • Organic Top of Funnel Content: How-Tos, Tutorials, Educational Content, Free Trial
    • Organic Middle Of Funnel Content: Free Cheatsheet, Free Quiz
    • Organic Bottom Of Funnel Content: Live Event
  • Email Marketing
    • Nurture Phase Content: 1 x Per Week
    • Pre-Launch & Launch Phase Content: 4 X Per Week
  • Live Launch Event (Conversion Asset):
    • Promoted via email and social media channels as well as one influencer marketing channel. (I believe that) ~50 showed up to the event or watched the replay, and 6 people purchased. Conversion rate = ~12%
  • Sales Page (Conversion Asset)
    • We used a long-form, conversion-optimized B2C sales page which came complete with product demos, a brand story, and a product overview video. You can see the sales page embedded within Value Proposition and Messaging Section above.
    • The product demonstration on the sales page directly proved the claim that the spreadsheet was 100x faster than the competitor, Google Sheets.

Partnerships

I personally was the influencer that supported this product launch. My audience is comprised of people from the data analytics, data science, and AI industry. By publishing a few of our pre-launch emails to my own channel, I was able to drive ~60 targeted leads for the product. Most of these people were data analysts and business analysts.

Evergreen Publishing Plan:

  • Blog: 1 x per week
  • Email: 1 x per week
  • Social Media (LinkedIn & Twitter): 4 x per week
  • Lead Magnet: Free quiz, free cheat sheet, free trial

 

Content Topics:

  • Blog: Topics covered financial industry trends, product features, spreadsheet analysis how-tos
  • Email: Emails covered financial industry trends, product features, spreadsheet analysis how-tos. They were also used to provide product updates, solicit user testimonials, and drive traffic to the quiz funnel.

 

Engagement / Success Metrics

  • Tripled email list size in 4 months (with a 37% open rate and 2% click rate) by designing and implementing a robust, community-focused email marketing strategy.
  • Led a small team on an acquisition-focused website development project to develop a robust 55-page website (including conversion-optimized sales pages, a quiz funnel, surveys, and an SEO-optimized blog) and then drove an 85x increase in website visitors in 7 months

 

Acquisition channels:

  • SEO-optimized blog content
  • Organic social media posts
  • Google Ads (PPC – Search)

 

Promotional Plan:

  • Generally, I would plan 1 sale or launch event every quarter and then run heavy organic nurture content in between these sale intervals. I was able to run one cycle of organic nurture and growth content before the project was closed out. This was not enough time to grow organically, but despite that I was able to triple the email list size in 4 months (with a 37% open rate and 2% click rate) by designing and implementing a robust, community-focused email marketing strategy.

 

  • Grew the SaaS user base almost 200x in 1 month by designing and implementing an “Acquisition, Activation, Retention, Revenue and Referral” funnel
  • Tripled email list size in 4 months (with a 37% open rate and 2% click rate) by designing and implementing a robust, community-focused email marketing strategy
  • Led a small team on an acquisition-focused website development project to develop a robust 55-page website (including conversion-optimized sales pages, a quiz funnel, surveys, and an SEO-optimized blog) and then drove an 85x increase in website visitors in 7 months
  • Drove the company past its “first dollar” revenue milestone within 2 months by designing and launching the company’s first Minimum Marketable Product.
  • Launched the company’s first Minimum Viable Product, which resulted in 1,100 new users in the first month
  • Conducted A/B testing + experimental optimizations to identify ideal ads segments and to validate our ICP

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