Ryan S.

Situation/Opportunity:

GumGum had 1 senior Detroit salesperson and 2 junior salespeople covering Minneapolis accounts when I'd started. Minneapolis was under-performing (35% to goal) and Detroit was overly dependent on auto revenue (more than 90%).  Also, prior to my arrival all Indiana and Ohio accounts had been moved from my region (Midwest) to the East region following a sales rep departure, further reducing my territory's ability to grow. A change in personnel and territory structure was needed to boost performance, but that required data-backed convincing of GumGum executives.

Action:

One Minneapolis salesperson moved to our West Coast office, and the other was let go for poor performance. I convinced our CFO, CRO, and HR team that we could accelerate growth by replacing the 2 junior Minneapolis salespeople with 1 senior salesperson with a larger network of established contacts. Additionally, I was able to get an extra salesperson hired in Detroit to cover not only all non-auto business, but to bring Indiana and Ohio back into our region's goals and revenue as well.

Result:

I was able to hire a senior Minneapolis saleswoman within 2 months, and within the next 15 months she achieved GumGum's all-time highest run rate in the Minneapolis sales territory. In Detroit, having a 2nd salesperson in-region caused a healthy competition between the 2 salespeople, landing GumGum 10 new business clients within a year, and renewing a stagnant relationship with automaker Stellantis 

Defining Metric:

Rebuilt Midwest sales team, tripling Minneapolis revenue to $1M+ in 15 months and landing 10+ new clients in Detroit—GumGum's top new biz territory in 2023 through strategic hiring. 

Situation/Opportunity:

Best Buy was concerned that Walmart was getting into the Consumer Electronics business in a bigger way, since Walmart's store sizes were enormous and total locations were increasing each month. The CMO of Best Buy, Barry Judge, approached my team about providing him with search and internet data about Walmart as a potential threat to Best Buy. What our data told us was Best buy had a much larger threat from a store with no physical locations - Amazon.

Action:

I presented BestBuy with the data they'd requested and showed them that Walmart only presented a threat in the low-price electronics categories where Best Buy's margin was already small. I then showcased the data around consumer's consumer electronic behavior online, and how it was clear that Amazon was already a huge competitor for Best Buy.

Result:

BestBuy's CMO politely thanked me and said, "When the day comes that someone can walk into a BestBuy store, look around, and then buy from Amazon on the spot, let me know." Several months later the first affordable smartphones were released, and within a year they were the pervasive. Customers were walking into Best Buy stores, looking at which TV they wanted to buy, and then going online while at Best Buy and purchasing the same TV cheaper from Amazon. "Showrooming" became a verb describing just that.  More importantly, Best Buy's CMO publicly admitted his mistake in not listening to my insight by posting on Twitter, "Last year Google told me this would happen and I didn't listen. My bad".   Within a year, Best Buy's ad spend on Google had nearly doubled, and within 2 years it was over 5 times it's previous level. 

Defining Metric:

Identified Amazon as Best Buy's top digital threat, influencing a 5X increase in Google ad spend to $50M+ annually after data-driven insights preempted rise of "showrooming" behavior.

Situation/Opportunity:

Target saw declining returns and increasing costs with their newspaper Sunday Circular and was risking losing funding from major brands who helped fund their circular like P&G, Kraft (now Kraft Heinz), and Johnson & Johnson.

Action:

I introduced the idea of "digital shelf space" to Target's brand relationship managers as well as their advertising team. In short, brands like Procter and Gamble could "own" Google search results for their products by running ads that not only drove customers to P&G's website, but to major chains where their products were sold (I.e. - Target)

Result:

The co-op campaign was a huge success at a fraction of the cost of the newspaper circular. Brands could measure clicks and purchases, and we ran 3rd party brand-lift studies to measure increases in brand awareness. This allowed Target to accelerate their phasing-out of the newspaper Sunday circular by almost 2 years 

Defining Metric:

Replaced Target’s costly print circular with co-op digital shelf space strategy, boosting measurable clicks, purchases, and brand lift—accelerating circular phase-out by nearly 2 years. 

Situation/Opportunity:

MBuy had both a profitability and morale problem when I took over as General Manager, leading to small profit margins and higher-than-desirable employee turnover. I quickly realized that the media planning, data science, and operations teams resented the business development (aka sales) team for selling-and-leaving client relationships while still reaping sizable commission benefits. I noticed that prior to me joining, MBuy also had a less than 20/80 revenue ratio of new to existing business, and new business retention after 1 year with MBuy was declining.

Action:

After getting employee feedback and talking with my key leaders, I built a compensation plan that bonused non business development teams bi-annually for hitting goals. Meanwhile, I reduced the business development team's commission on any business that had been with MBuy for over 1 year, and increase their commission percentage on new business, with an additional kicker if the new business client renewed following their initial contract. I also worked with our data science team to build a data-and-anlaytics-only product for prospective clients who already ran their own media.  Next I reduced the size of the business development team and increased hiring on the data science and media teams to support current clients and sell our data platform product. Most importantly, I showed Mediaocean's CFO and CEO how my changes would yield more profitability if we were to win more new business, and create more cost savings if we continued to rely on existing business.

Result:

It took nearly six months to convince the C-level executives and the MBuy leaders and business development teams why this would be good for them, but when they saw it in action, the "proof was in the pudding." The changes were an overwhelming success, increasing both top line and bottom line revenue. 

Defining Metric:

MBuy saw it's best topline ever at $70MM annually, and it's best bottom line as well (confidential data). Profit margin also increased from 14% to 27% without increasing headcount. MBuy had greater than 90% retention rate of average-to-top performers

Situation/Opportunity:

I led the pitch to win new business for Oasis Financial, a pre-settlement legal company who had very aggressive sales and profitability goals. As such, they demanded contract terms that I knew were not beneficial to MBuy. I also knew their contract terms were unrealistic based on the personnel and data support they needed from a managed service agency, and Oasis wasn't willing to be flexible on those terms.

Action:

I politely and professionally removed MBuy from consideration to win the business, even though we were finalists. Knowing the competitor that Oasis chose did not have the resources to deliver on what Oasis needed to reach revenue goals, I stayed in touch with the key decision makers, but never asked them to reconsider their decision or told them their contract terms were unreasonable. After 6 months, I could see Oasis was becoming unhappy with the agency they chose, 3 months later I sat down with the Oasis leaders to discuss what mutually favorable terms could look like if we worked together. 3 months after that I closed the Oasis deal.

Result:

I hired an additional research for managing search, Oasis's key media revenue driver, and Oasis saw their best revenue and profit margins ever because of our successful search program. Oasis became MBuy's 3rd-largest advertiser nearly overnight, and loved working with us. 

Defining Metric:

Oasis's ROI for their overall program exceeded their aggressive standard (5:1 revenue to cost ratio) and Oasis's media run rate with MBuy was over $6MM annually, making them our 3rd largest advertiser.

Situation/Opportunity:

I was moved from Business Development into a Sales role with aggressive goals at startup (and relatively unknown brand) Boost Media with almost no book of running business behind me. I needed to go from less than $10,000/mo in running revenue to over $100,000 as quickly as possible, since both my job security and the company's financial viability hung in the balance. Boost's core product, a creative optimization service for Google and Bing search could easily show quantifiable results, but scale for even medium-sized clients was an issue.

Action:

I focused solely on ad agencies, who could potentially adopt our SaaS technology across many clients. More specifically, I leveraged existing relationships and made new relationships with data science and analytics teams within these agencies. It was easier to get an audience with data teams vs media teams and easier still to speak their data-and-performance languageto convince them why they needed our service. In one case, I persuaded a key senior influencer - the Director of Data and Insights of iProspect to lean on all of iProspect's clients to use our service. By the time I spoke with media teams, they were already bought into our benefits because they'd been persuaded by that senior leader internally.

Result:

Within 60 days, I landed my first client from iProspect and within 6 months, that increased to 7 iProspect clients and 6 clients across 2 more agencies. My run rate went 10X from just under $10,000/mo to just under $100,000. 

Defining Metric:

Grew SaaS revenue 10X in 6 months at Boost Media by securing 13 agency clients—including 7 from iProspect—via strategic engagement with analytics leaders to drive 5X media savings.

Situation/Opportunity:

DoubleClick was a media rep firm before it became a technology company, and I worked for the media arm. Doubleclick's network was largely composed of websites of big offline brands like FoodTV and Bloomberg who were just getting started online.  We turned many websites away who had bigger online traffic because they didn't have the brand cache that big advertisers wanted to associate their brands with. The challenge was not only that if we didn't meet a website's revenue expectations, they canceled their contract, but if we exceeded expectations they often used the profit to hire their own sales staff, often poaching their own people. But a few of us at DoubleClick saw the value of reaching engaged customers who were loyal to websites that didn't have long standing offline traditional brand presence (I.e. - IMDB, TopSecretRecipes, and many others)

Action:

I led a team that pioneered a second DoubleClick network of websites with less offline brand cache. Because these websites had less brand presence and rarely had their own internal sales efforts, we were able to negotiate contracts where DoubleClick saw a 55%/45% or even 60%/40% revenue split in our favor, compared to the 20-30% we were getting with our large, branded sites. We also were able to accept and service more than 10,000 website partners, compared to the mere dozens in DoubleClick's original network.

Result:

Advertisers quickly saw this second network - they connected with more engaged customers at a greater scale for a lower cost. In fact, this network based on audience targeting was the precursor to the programmatic advertising we use today. Additionally, when the internet "bubble burst" in 2000-2001, my network saved DoubleClick's US business. My team was so successful that I spent the summer of 2001 working at all of DoubleClick's European offices (I was based in London) working with the local teams to implement the same model we'd created stateside. 

Defining Metric:

Earning 60% of every dollar while using fewer people resources to manage a much higher volume of websites made our network more profitable than DoubleClick's original network, and it literally saved our media business.

Situation/Opportunity:

Like many companies, Google employed summer undergrads to help vet young talent as well as take relieve other team members of every day tasks. Google decided to experiment with a "Graduate Program" where post-grad MBAs would intern with the hopes that we could develop more strategic talent for Google's future. However, that's as far as the experiment was thought through - no jobs, tasks, metrics of success, or even ideal program goals had been defined.

Action:

I volunteered to pioneer this program with 2 different MBA interns working for me. This meant I had to define end-of-program goals for both the candidate and for Google, assign tasks to meet those goals, have regular meetings and check-ins on progress, and create an environment where talented candidates wanted to work at Google when they completed their MBAs.

Result:

In the first year I successfully incorporated the candidates to the Google culture by including them in meetings with my team, giving them 1:1 time with senior Google managers, taking them on team bonding events outside the office, and even exposing them to some of our clients. In that initial year, I also learned that I had assigned some goals and tasks that were either too vague or too remedial, yet both my candidates wanted to work full-time at Google following graduation. In year 2 I leveraged what worked and either scrapped or tweaked what didn't to create a more ideal program where candidates had summer "thesis" projects to complete that benefited not only them but produced usable data, reports, or tools for my team and/or our clients.  The success of this program led to much greater investments in students-as-current-and-future resources for Google . Here's how it looks today, 12 years after I pioneered it. -https://www.google.com/about/careers/applications/students 

Defining Metric:

Pioneered Google’s MBA intern program, designing goals, structure, and deliverables; success led to program-wide expansion across departments, including Engineering, due to superior ROI.

Situation/Opportunity:

Chevron wanted to connect with a younger (under 35) demographic who was concerned about the oil industry's use of fossil fuels and the potential negative impact that Big Oil companies were having on the planet in the wake of the 2010 BP Gulf of Mexico oil spill. Chevron wanted to show that they were concerned about world causes and highlight their donations to fight AIDS.

Action:

I sold a YouTube homepage takeover for December 1st 2013 to Chevron for World AIDS Day where they could advertise on the front door of the world's largest video site to create favorable brand awareness and influence.

Result:

Chevron received just over 100 MILLION ad impressions on the YouTube homepage that day, driving massive amounts of views of their other YouTube videos as well. This was the first time an oil or energy company spent over $500,000 in one day on Google or YouTube.