A few years ago, building a bottom-up SaaS company – defined as a firm where the average purchasing decision is made without ever speaking to a salesperson – was a novel concept. Today, by our count, at least 30% of the Cloud 100 are now bottom-up.
For the first time, individual employees are influencing the tooling decisions of their companies versus having these decisions mandated by senior executives. Self-serve businesses thrive on this momentum, leveraging individuals as their evangelists, to grow from a single use-case to small teams, and ultimately into whole company deployments.
In a truly self-service model, individual users can sign up and try the product on their own. There is no need to get compliance approval for sensitive data or to get IT support for integrations — everything can be managed by the line-level users themselves. Then that person becomes an internal champion, driving adoption across the organization.
Today, some of the most well-known software companies such as Datadog, MongoDB, Slack and Zoom, to name a few, are built with a primarily bottom-up product-led sales approach.
In this piece, we will take a closer look at this trend — and specifically how it has fundamentally altered pricing — and at a framework for mapping pricing to customer value.
In a bottom-up SaaS world, pricing has to be transparent and standardized (at least for the most part, see below). It’s the only way your product can sell itself. In practice, this means you can no longer experiment as you go, with salespeople using their gut instinct to price each deal. You need a concrete strategy that aligns customer value with pricing.
To do this well, you need to deeply understand your customers and how they use your product. Once you do, you can “MAP” them to help align pricing with value.
The MAP customer value framework requires deeply understanding your customers in order to clearly identify and articulate their needs across Metrics, Activities and People.
Not all elements of MAP should determine your pricing, but chances are that one of them will be the right anchor for your pricing model:
Metrics: Metrics can include things like minutes, messages, meetings, data and storage. What are the key metrics your customers care about? Is there a threshold of value associated with these metrics? By tracking key metrics early on, you’ll be able to understand if growing a certain metric increases value for the customer. For example:
Activity: How do your customers really use your product and how do they describe themselves? Are they creators? Are they editors? Do different customers use your product differently? Instead of metrics, a key anchor for pricing may be the different roles users have within an organization and what they want and need in your product. If you choose to anchor on activity, you will need to align feature sets and capabilities with usage patterns (e.g., creators get access to deeper tooling than viewers, or admins get high privileges versus line-level users). For example:
Milana Lewis, CEO and co-founder of music tech startup Stem, started the fundraising process long before she actually asked any investors for money (dig the well before you’re thirsty — it’s the best way). She recommends that other founders do the same.
Ten years ago, Milana started working at United Talent Agency (UTA), one of the world’s leading talent agencies. When tasked with finding the best tools and technologies that UTA’s clients could use to self-distribute their work, she discovered a glaring gap.
“There were all these tools built for the distribution of content, monetization of content and audience development,” she says. “The last piece missing was the financial aspect.” The entertainment industry desperately needed a platform that would help artists manage the financial side of their business — and that’s how the idea for Stem was born.
Because UTA had its own investment branch, called UTA Ventures, Milana’s job also introduced her to some brilliant investors. Years later, when it was time to fundraise for Stem, those connections played a pretty big role.
In an episode of How I Raised It, Milana shared how Stem has landed some superstar investors and raised a little under $22 million.
Milana’s involvement with UTA Ventures exposed her to the investor experience and put her in the same room as people like Gary Vaynerchuk, Jonathon Triest from Ludlow Ventures, Anthony Saleh from Wndrco and Scooter Braun.
After meeting them the first time, she made sure to nurture those relationships, and she was “honest and vulnerable” about the fact that she wanted to be an entrepreneur one day.
“It’s amazing how much people will help and support you along in that journey,” Milana says. Investors “get excited about making early-stage investments because they want to identify that person before anyone else does.”
As her idea for Stem came together, she shared that with them, too. Over the course of a year, she provided regular updates on her vision, like how she was building out her team, and she also called them for occasional advice.
By the time she approached some of them for funding, she didn’t even need to present a full pitch. By then, they already knew enough about Stem, and about Milana as a businesswoman. Her pitch meeting with Gary Vaynerchuk — the first person to invest — ended up being just 15 minutes long.
“I brought people on my entrepreneurial journey in the beginning,” Milana says. “The biggest piece of advice I could give is to start raising a year before you start raising. Start building relationships and data points.”
Image Credits: Nathan Beckord (opens in a new window)
For each round, Milana put together a lead list — a list of potential investors who she either met socially or through business. Each time, she wanted to have at least 100 names on this list.
Digital PR is an excellent strategy to pair with content marketing, especially if your goals include increasing your brand awareness and improving your backlink portfolio.
When you create excellent content and pitch it to writers, you not only get great media coverage, but you get the link back to your project and the authority that comes with being mentioned in a trusted publication.
This earned media tactic is very effective — but it isn’t easy.
If you get any part of it wrong, your chances of success decrease dramatically. If you’ve run into roadblocks, make sure you’re not making any of these mistakes with your content or your pitching.
Sure, it’s easy to say the news only wants to cover material that is, well, news worthy.
But what does that actually mean?
For content marketers, it usually refers to three criteria: timeliness, relevance and significance.
But there’s a catch: Most content marketing programs don’t have journalists devoted to breaking news like actual media outlets do. So how can you create content that is truly newsworthy without the resources of a newsroom?
By creating and analyzing your own data.
If your brand provides a fresh data set or a new analysis of existing data, then you’re the sole owner of information, and you can offer it exclusively to publications. This makes your pitch much more interesting.
This tactic is a combination of original content marketing and digital PR.
But the content can’t just be timely. It also has to be relevant to the writer you’re pitching and that writer’s audience. I’ll explain more on that in #4.
Finally, significance, which refers to the impact it has on the audience. When you think of local news, this is why they report on things like traffic jams and school closures: It directly affects the daily lives of the people watching and listening.
Alternatively, your data can be significant to writers covering specific beats. For example, for our client ZenBusiness, we surveyed Americans and asked what they thought about the government’s relief packages for COVID-19.
While ZenBusiness operates in the office/work niches, this new insight into American perspective was appealing to the political publication The Hill.
Image Credits: Fractl (opens in a new window)
Significance is tough criteria from a brand perspective, but if you’re able to offer brand-new insights, it’s certainly not impossible.
Imagine a stranger handing you a book with a blank cover and saying, “Here, you’ll find this interesting.” Would you read the whole book?
Many consumers might think Noom or Weight Watchers are industry leaders with their nonstop commercials, but neither is the fastest-growing weight management program.
Over the past year, nutrition app Lifesum has acquired users at nearly twice the rate of both Noom and Weight Watchers, according to statistics from Sensor Tower, the independent market intelligence for the mobile app economy.
Over this past summer, we surpassed Noom on the global scale with 45 million users. More impressively, we accomplished this without any TV buys. That’s right — no multimillion dollar ad campaigns, allowing us to redistribute precious marketing dollars to other growth projects.
Here’s a closer look at the three growth marketing tactics I credit with helping us scale Lifesum over the last 36 months. It’s a strategy any startup can use, regardless of size or budget.
Generations approach products differently. It’s important for startups to understand the different generational approaches of their customers. Startups that spend time thinking and strategizing about where generational trends are going will scale faster.
Here’s a closer look at the three growth marketing tactics I credit with helping us scale Lifesum over the last 36 months. It’s a strategy any startup can use, regardless of size or budget.
Millennials and Generation Z are now the largest consumer market in the world, so you can’t ignore them if you want to scale. With Lifesum these generations have helped our brand surpass the older and well-established competitors. We achieved this by intimately understanding how they view health and fitness.
Gen Z and millennials are all about empowerment. They grew up with Google and Facebook, having information at their fingertips. They are far less likely to be moved by a TV commercial since they desire to discover the world on their own.
In our industry, we’ve learned millennials and Gen Z don’t want a one-size-fits-all weight loss program or to count calories like their parents did 20 years ago. As millennials and Gen Z started embracing keto, intermittent fasting and pescatarian diets, our nutrition team had already created tailored programs to help them stick with it.
As a brand, it’s important to look ahead and anticipate what is coming next. This also applies to marketing your product. If you get in early with emerging marketing platforms, you will save money and potentially reach more early adopters.
Recently I’ve seen people mention the difficulty of generating content that can garner massive attention and links. They suggest that maybe it’s better to focus on content without such potential that can earn just a few links but do it more consistently and at higher volumes.
In some cases, this can be good advice. But I’d like to argue that it is very possible to create content that can consistently generate high volumes of high-authority links. I’ve found in practice there is one truly scalable way to build high-authority links, and it’s predicated on two tactics coming together:
How can you use new techniques to generate consistent and predictable content marketing wins?
The key is data.
It’s my strong opinion that there’s no shortcut to earning press mentions and that only truly new, newsworthy and interesting content can be successful. Hands down, the simplest way to predictably achieve this is through a data journalism approach.
One of the best ways you can create press-earning, data-focused content is by using existing data sets to tell a story.
There are tens of thousands — perhaps hundreds of thousands — of existing public datasets that anyone can leverage for telling new and impactful data-focused stories that can easily garner massive press and high levels of authoritative links.
The last five years or so have seen huge transparency initiatives from the government, NGOs and public companies making their data more available and accessible.
Additionally, FOIA requests are very commonplace, freeing even more data and making it publicly available for journalistic investigation and storytelling.
Because this data usually comes from the government or another authoritative source, pitching these stories to publishers is often easier because you don’t face the same hurdles regarding proving accuracy and authoritativeness.
The accessibility of data provided by the government especially can vary. There are little to no data standards in place, and each federal and local government office has varying amounts of resources in making the data they do have easy to consume for outside parties.
The result is that each dataset often has its own issues and complexities. Some are very straightforward and available in clean and well-documented CSVs or other standard formats.
Unfortunately, others are often difficult to decode, clean, validate or even download, sometimes being trapped inside of difficult to parse PDFs, fragmented reports or within antiquated querying search tools that spit out awkward tables.
Deeper knowledge of web scraping and programmatic data cleaning and reformatting are often required to be able to accurately acquire and utilize many datasets.
Lead Edge Capital, a software-focused venture firm with one office in New York and another in California, was founded just 11 years ago. Yet it’s already managing $3 billion in assets through a process that founder Mitchell Green half-kiddingly refers to as “rinse and repeat.”
As he describes its model, Lead Edge raises money from wealthy, networked individuals, then it claws its way into companies, helps them, turns them into valuable references, and when those companies sell or go public, the firm raises more money from people who like the firm’s returns.
It sounds simple but it isn’t, says Green, who cut his teeth as an associate at Bessemer Venture Partners and at a Tiger Fund-affiliate called Eastern Advisors. Managing 500 investors, which is now the case, is “harder than it looks.”
That’s true even with two partners: Brian Neider, who first crossed paths with Green at Bessemer, and Nimay Mehta, who joined the firm in 2011. That’s true despite a dozen employees who Green says are “zero to five years out of college” and cold-call companies all day,
It’s a lot of work, even with four investors who are also operating partners and who, in that capacity, sometimes serve as board members on behalf of Lead Edge. These are former eBay president Lorrie Norrington, former Netsuite CFO Ron Gill, former Dell CFO Jim Schneider, and former Dell president Paul Bell. (“If you’ve already got a couple of VCs on your board,” says Green, “I think the company gets more benefit from putting operators on the board.”)
Not that anyone is complaining. On the contrary, Lead Edge has been having a very good run, which explains how its fund sizes have so quickly ballooned, from a $52 million debut vehicle to a $138 million fund, a $290 million fund, a $520 million vehicle, and now a $950 million fifth fund. (Lead Edge also spins up special purpose vehicles on the side one to two times a year when it wants an especially big bite of a certain company.)
Some of its largest returns by dollars have come via Alibaba’s IPO, Spotify’s IPO, and the sale of Duo Security to Cisco, companies on which it made big bets. Green has said the firm invested $300 million into Alibaba in the years leading up to its IPO; more than $150 million into Spotify in the years leading up to its IPO; and more than $90 million into Duo.
This year is proving fortuitous to Lead Edge’s backers, too, including thanks to the recent direct listing of Asana and the sale of Signal Sciences to Fastly.
That’s saying nothing about the Alibaba affiliate ANT Group, into which Lead Edge has poured $160 million over the years and that’s now expected to become the world’s largest IPO (although the offering has been delayed for now by China’s securities regulator).
Given these wins, it’s maybe it’s not so surprising that the firm’s investor base would continue to build on itself, and in the process turn into a highly competitive advantage for the firm, according to Green.
Indeed, when asked how Lead Edge differentiates itself from other growth-stage investors, he cites the firm’s pool of backers, which includes former Xerox CEO Anne Mulcahy, former Charles Schwab CEO David Pottruck, and former ESPN CEO Steve Bornstein, among the hundreds of other individuals who’ve written checks to Lead Edge that range from $250,000 to $50 million.
While he won’t say who some of the biggest of those investors are in terms of dollars committed, he has no qualms in crediting them collectively with the firm’s success — or going out of his way to keep them happy. Last night, for example, he played host to some of them at his Southern California home. He doesn’t seem to mind it.
“People want us for our LP network,” says Green. “That’s what we’re known for, 100%.”
Podcast advertising growth is inhibited by three major factors:
Because of these limiting factors, it’s currently more of an art than a science to piece disparate data from multiple sources, firms, agencies and advertisers, into a somewhat conclusive argument to brands as to why they should invest in podcast advertising.
There were several resources that released updates based on what they saw in terms of consumption when COVID-19 hit. Hosting platforms, publishers and third-party tracking platforms all put out their best guesses as to what was happening. Advertisers’ own podcast listening habits had been upended due to lockdowns; they wanted to know how broader changes in listening habits were affecting their campaigns. Were downloads going up, down or staying the same? What was happening with sports podcasts, without sports?
Read part 1 of this article, Podcast advertising has a business intelligence gap, on TechCrunch.
At Right Side Up, we receive and analyze all of the available research from major publishers (Stitcher, aCast), to major platforms (Megaphone) and third-party research firms (Podtrac, IAB, Edison Research). However, no single entity encompasses the entire space or provides the kind of interactive, off-the-shelf customizable SaaS product we’d prefer, and that digitally native marketers expect. Plus, there isn’t anything published in real-time; most sources publish once or twice annually.
So what did we do? We reached out to trusted publishers and partners to gather data around shifting consumption due to COVID-19 ourselves, and determined that, though there was a drop in downloads in the short term, it was neither as precipitous nor as enduring as some had feared. This was confirmed by some early reports available, but how were we to evidence our own piecewise sample with another? Moreover, how could you invest 6-7 figures of marketing dollars if you didn’t have the firsthand intelligence we gathered and our subject matter experts on deck to make constant adjustments to your approach?
We were able to piece together trends we’re seeing that point to increased download activity in recent months that surpass February/March heights. We’ve determined that the industry is back on track for growth with a less steep, but still growing, listenership trajectory. But even though more recent reports have been published, a longitudinal, objective resource has not yet emerged to show a majority of the industry’s journey through one of the most disruptive media environments in recent history.
There is a need for a new or existing entity to create cohesive data points; a third party that collects and reports listening across all major hosts and distribution points, or “podcatchers,” as they’re colloquially called. As a small example: Wouldn’t it be nice to objectively track seasonal listening of news/talk programming and schedule media planning and flighting around that? Or to know what the demographics of that audience look like compared to other verticals?
What percentage increase in efficiency and/or volume would you gain from your marketing efforts in the channel? Would that delta be profitable against paying a nominal or ongoing licensing or research fee for most brands?
These challenges aren’t just affecting advertisers. David Cohn, VP of Sales at Megaphone, agrees that “full transparency from the listening platforms would make our jobs easier, along with everyone else’s in the industry. We’d love to know how much of an episode is listened to, whether an ad is skipped, etc. Along the same lines, having a central source for [audience] measurement would be ideal — similar to what Nielsen has been for TV.” This would also enable us to understand cross-show ad frequency, another black box for advertisers and the industry at large.
There are sizable, meaningful gaps in the knowledge collection and publication of podcast listening and engagement statistics. Coupled with still-developing advertising technology because of the distributed nature of the medium, this causes uncertainty in user consumption and ad exposure and impact. There is also a lot of misinformation and misconception about the challenges marketers face in these channels.
All of this compounds to delay ad revenue growth for creators, publishers and networks by inhibiting new and scaling advertising investment, resulting in lost opportunity among all parties invested in the channel. There’s a viable opportunity for a collective of industry professionals to collaborate on a solution for unified, free reporting, or a new business venture that collects and publishes more comprehensive data that ultimately promotes growth for podcast advertising.
Podcasts have always had challenges when it comes to the analytics behind distribution, consumption and conversion. For an industry projected to exceed $1 billion in ad spend in 2021, it’s impressive that it’s built on RSS: A stable, but decades-old technology that literally means really simple syndication. Native to the technology is a one-way data flow, which democratizes the medium from a publishing perspective and makes it easy for creators to share content, but difficult for advertisers trying to measure performance and figure out where to invest ad dollars. This is compounded by a fractured creator, server and distribution/endpoint environment unique to the medium.
Because podcasts lag other media channels in business intelligence, it’s still an underinvested channel relative to its ability to reach consumers and impact purchasing behavior.
For creators, podcasting has begun to normalize distribution analytics through a rising consolidation of hosts like Art19, Megaphone, Simplecast and influence from the IAB. For advertisers, though, consumption and conversion analytics still lag far behind. For the high-growth tech companies we work with, and as performance marketers ourselves, measuring the return on investment of our ad spend is paramount.
Because podcasts lag other media channels in business intelligence, it’s still an underinvested channel relative to its ability to reach consumers and impact purchasing behavior. This was evidenced when COVID-19 hit this year, as advertisers that were highly invested or highly interested in investing in podcast advertising asked a very basic question: “Is COVID-19, and its associated lifestyle shifts, affecting podcast listening? If so, how?”
We reached out to trusted partners to ask them for insights specific to their shows.
Nick Southwell-Keely, U.S. director of Sales & Brand Partnerships at Acast, said: “We’re seeing our highest listens ever even amid the pandemic. Across our portfolio, which includes more than 10,000 podcasts, our highest listening days in Acast history have occurred in [July].” Most partners provided similar anecdotes, but without centralized data, there was no one, singular firm to go to for an answer, nor one report to read that would cover 100% of the space. Almost more importantly, there is no third-party perspective to validate any of the anecdotal information shared with us.
Publishers, agencies and firms all scrambled to answer the question. Even still, months later, we don’t have a substantial and unifying update on exactly what, if anything, happened, or if it’s still happening, channel-wide. Rather, we’re still checking in across a wide swath of partners to identify and capitalize on microtrends. Contrast this to native digital channels like paid search and paid social, and connected, yet formerly “traditional” media (e.g., TV, CTV/OTT) that provide consolidated reports that marketers use to make decisions about their media investments.
The lasting murkiness surrounding podcast media behavior during COVID-19 is just one recent case study on the challenges of a decentralized (or nonexistent) universal research vendor/firm, and how it can affect advertisers’ bottom lines. A more common illustration of this would be an advertiser pulling out of ads, for fear of underdelivery on a flat rate unit, missing out on incremental growth because they were worried about not being able to get download reporting and getting what they paid for. It’s these kinds of basic shortcomings that the ad industry needs to account for before we can hit and exceed the ad revenue heights projected for podcasting.
Advertisers may pull out of campaigns for fear of under-delivery, missing out on incremental growth because they were worried about not getting what they paid for.
If there’s a silver lining to the uncertainty in podcast advertising metrics and intelligence, it’s that supersavvy growth marketers have embraced the nascent medium and allowed it to do what it does best: personalized endorsements that drive conversions. While increased data will increase demand and corresponding ad premiums, for now, podcast advertising “veterans” are enjoying the relatively low profile of the space.
As Ariana Martin, senior manager, Offline Growth Marketing at Babbel notes, “On the other hand, podcast marketing, through host read ads, has something personal to it, which might change over time and across different podcasts. Because of this personal element, I am not sure if podcast marketing can ever be transformed into a pure data game. Once you get past the understanding that there is limited data in podcasting, it is actually very freeing as long as you’re seeing a certain baseline of good results, [such as] sales attributed to podcast [advertising] via [survey based methodology], for example.”
So how do we grow from the industry feeling like a secret game-changing channel for a select few brands, to widespread adoption across categories and industries?
Below, we’ve laid out the challenges of nonuniversal data within the podcast space, and how that hurts advertisers, publishers, third-party research/tracking organizations, and broadly speaking, the podcast ecosystem. We’ve also outlined the steps we’re taking to make incremental solutions, and our vision for the industry moving forward.
In search of a rationale to how such a buzzworthy growth channel lags behind more established media types’ advertising revenue, many articles will point to “listener” or “download” numbers not being normalized. As far as we can tell at Right Side Up, where we power most of the scaled programs run by direct advertisers, making us a top three DR buying force in the industry, the majority of publishers have adopted the IAB Podcast Measurement Technical Guidelines Version 2.0.
This widespread adoption solved the “apples to apples” problem as it pertained to different networks/shows valuing a variable, nonstandard “download” as an underlying component to their CPM calculations. Previous to this widespread adoption, it simply wasn’t known whether a “download” from publisher X was equal to a “download” from publisher Y, making it difficult to aim for a particular CPM as a forecasting tool for performance marketing success.
However, the IAB 2.0 guidelines don’t completely solve the unique-user identification problem, as Dave Zohrob, CEO of Chartable points out. “Having some sort of anonymized user identifier to better calculate audience size would be fantastic — the IAB guidelines offer a good approximation given the data we have but [it] would be great to actually know how many listeners are behind each IP/user-agent combo.”
A second area of business intelligence gaps that many articles point to as a cause of inhibited growth is a lack of “proof of delivery.” Ad impressions are unverifiable, and the channel doesn’t have post logs, so for podcast advertisers the analogous evidence of spots running is access to “airchecks,” or audio clippings of the podcast ads themselves.
Legacy podcast advertisers remember when a full-time team of entry-level staffers would hassle networks via phone or email for airchecks, sometimes not receiving verification that the spot had run until a week or more after the fact. This delay in the ability to accurately report spend hampered fast-moving performance marketers and gave the illusion of podcasts being a slow, stiff, immovable media type.
Systematic aircheck collection has been a huge advent and allowed for an increase in confidence in the space — not only for spend verification, but also for creative compliance and optimization. Interestingly, this feature has come up almost as a byproduct of other development, as the companies who offer these services actually have different core business focuses: Magellan AI, our preferred partner, is primarily a competitive intelligence platform, but pivoted to also offer airchecking services after realizing what a pain point it was for advertisers; Veritone, an AI company that’s tied this service to its ad agency, Veritone One; and Podsights, a pixel-based attribution modeling solution.
Last, competitive intelligence and media research continue to be a challenge. Magellan AI and Podsights offer a variety of fee and free tiers and methods of reporting to show a subset of the industry’s activity. You can search a show, advertiser or category, and get a less-than-whole, but still directionally useful, picture of relevant podcast advertising activity. While not perfect, there are sufficient resources to at least see the tip of the industry iceberg as a consideration point to your business decision to enter podcasts or not.
As Sean Creeley, founder of Podsights, aptly points out: “We give all Podsights research data, analysis, posts, etc. away for free because we want to help grow the space. If [a brand], as a DIY advertiser, desired to enter podcasting, it’s a downright daunting task. Research at least lets them understand what similar companies in their space are doing.”
There is also a nontech tool that publishers would find valuable. When we asked Shira Atkins, co-founder of Wonder Media Network, how she approaches research in the space, she had a not-at-all-surprising, but very refreshing response: “To be totally honest, the ‘research’ I do is texting and calling the 3-5 really smart sales people I know and love in the space. The folks who were doing radio sales when I was still in high school, and the podcast people who recognize the messiness of it all, but have been successful at scaling campaigns that work for both the publisher and the advertiser. I wish there was a true tracker of cross-industry inventory — how much is sold versus unsold. The way I track the space writ large is by listening to a sample set of shows from top publishers to get a sense for how they’re selling and what their ads are like.”
Even though podcast advertising is no longer limited by download standardization, spend verification and competitive research, there are still hurdles that the channel has not yet overcome.
The conclusion to this article, These 3 factors are holding back podcast monetization, is available exclusively to Extra Crunch subscribers.
Even when you’re excellent at making the sale, you still need people to know you exist in the first place.
Content is excellent at making the case for your product or service, but it also excels at providing value to potential customers in a more tangential way, introducing them to your brand and building awareness and authority.
Here’s how utilizing content marketing and digital PR can make huge strides in getting your brand name out there.
When on-site content you created ranks well in the search engine results pages (SERPs), that doesn’t just mean you get more traffic (although that’s certainly a major benefit).
You’re also getting your brand name in front of searchers because you’re appearing in the results. You’re building authority because Google appears to believe you have the best answer for their query. You’re giving the searcher and answer to their question and beginning to build trust.
So how do you know which keywords/topics to target and what kind of content to create? You perform keyword research, which basically means examining what keywords people are searching for, how many people search for them per month and how hard it’ll be to rank for them.
When your goal is to build awareness, it’s important that the keywords and topics you target have high volume. In other words, they’re searched a lot. Awareness objectives mean reaching as many people as possible so more people know that your brand exists and begin to understand what it’s about.
There’s definitely a lot of talk about SPACs these days. But the tried-and-true IPO is still the long-term liquidity goal for most tech startups. CEOs dream of ringing the bell on the floor of the New York Stock Exchange, or seeing their face splashed across Nasdaq’s giant video screen in Times Square. Late last month, five high-profile tech companies filed on the same day to go public through traditional IPOs, presumably gunning to get out before the November election.
There is obviously a ton of operational, financial and regulatory preparation that goes into a successful initial public offering. But one aspect of IPO planning that often gets short shrift, particularly at B2B-focused companies chasing relatively niche buyer audiences, is branding and communications. As the head of marketing and communications for a big investment firm, I see this all the time. I believe companies who skimp here are throwing away significant equity value.
Simply put, a highly public financing event like an IPO is an enormous branding opportunity for most companies. It’s a free pass for companies to tell their stories to a huge, global audience and rack up high-level press coverage — both at the time of the IPO and in the future, since many publications (like my former employer, the Wall Street Journal) often focus on coverage of larger, publicly traded companies.
Why do so many companies fall down in this area? I think a lot of it has to do with the broader shift toward data-driven, online marketing and away from branding at many companies. Because highly technical companies in areas like hybrid-cloud computing or DevSecOps (yes, that’s a thing) often struggle in their early days to get journalists interested in their stories, they never make communications a priority inside the company. This comes back to haunt them when, all of the sudden, they’ve filed an S-1 and their exec team has zero experience explaining the company’s story in clear, persuasive terms to a general audience.
But smart companies can avoid this trap. Here are five ways you can get the most branding bang out of your tech IPO, no matter how arcane your company’s business is.
This is honestly the most important point to take away here. Successful PR and communications around an IPO are a result of long-term planning that starts at least 12 to 18 months before you file your offering document with the SEC. Once you think an IPO is in the offing, take a hard look at both your (1) marketing/communications staffing and (2) your existing digital footprint.
Orchard, the tech-forward residential real estate platform, has today announced the close of a $69 million Series C funding led by Revolution Growth. Existing investors FirstMark Capital, Navitas, Accomplice and Juxtapose also participated in the round, which brings the company’s total funding to $138 million.
Orchard (formerly Perch) launched in 2017 on a mission to digitize the entire experience of buying or selling a home. They focused initially (and still) on ‘dual trackers’, which essentially means that they are home buyers who are also in the process of selling their existing home.
As you might expect, the process of doing both at the same time can be incredibly tedious and, at times, costly. Orchard makes an offer on the buyers’ home with a price that’s guaranteed for 90 days — the company says the vast majority of those homes sell at market price before that 90-day period is over.
Orchard’s product suite also includes tools for searching for homes, title and mortgage.
The search products, in particular, stand out among a crowded space of property search tools. For example, Orchard users can search homes by the room that’s most important to them, putting the Kitchen or the Backyard as the lead image on their listings. Orchard also uses machine learning to suggest more personalized listings.
Orchard cofounder and CEO Court Cunningham had this to say in a prepared statement:
In the same way Amazon has fundamentally changed retail, and Carvana has innovated the car buying experience, Orchard is putting the customer first and modernizing the home buying and selling transaction. We’re thrilled to have a partner in Revolution Growth who has extensive experience working with transformative growth stage consumer businesses that are upending traditional industries. In the year ahead, we’ll be launching an exciting suite of new products and services that further modernize the home purchase experience, while also offering our services to new markets throughout the country.
In the release, the company said it would be using the investment to further expand the product portfolio and grow the team in markets like New York, Texas, Colorado and Georgia, as well as move into new states.