The total size of the cloud Software-as-a-Service (SaaS) global market is expected to reach 145 billion U.S. dollars by the end of 2021. That means there’s a buzzing interest among entrepreneurs to create SaaS applications and new ones emerge almost daily because of the convenience of their delivery model. With no installation, updates, or compatibility issues, SaaS products are a preferred choice for plenty of users.
However, when it comes to developing SaaS software, many entrepreneurs face a wide range of challenges that can often lead to expensive mistakes – and even failures. Solving these challenges strategically, or avoiding them altogether, requires knowledge of the process and the most important steps that will take you in the right direction.
In this article, we’ve covered 4 key steps of creating a SaaS product with an overview of both the product ideation and development processes. Although there are no guarantees for building a successful product, these steps outline a straightforward process that successful SaaS entrepreneurs have used – and continue to use – to bring successful solutions to market.
Create a Development Methodology and Team
To turn your product idea into a successful SaaS solution, you need to figure out the technical side of the project. The basis of your software development process is essentially having a food workflow, which requires a good branching model if you use Git. That means the development team should be experienced with basic Git concepts like pull and merge and more specific functions like, for example, the Git rename branch method, among others.
You should note that outsourcing your core product development is not recommended as it is often risky. Since a freelancer’s goals can be significantly different than yours, they might not be as invested in the product as you or someone else with a stake in the business is. That’s why it’s best to create an in-house team and hire software developers that will act more as partners than freelancers.
Develop a Solution to a Problem
Before you start developing your product, you should make sure there is a clear problem you’re addressing and a solution that solves it. The best way to start is by analyzing the market to look at competitors, demand, and your target audience. You will then need to work on identifying the core values and pain points of your future target audience to craft a one-stop-shop solution that addresses all of their needs.
When deciding which problem is worth addressing, there are a few things to consider. First, you should make sure it’s a problem you can relate to; that will ensure you fully appreciate the problem and can solve it in the best way possible. Second, you should find a problem that you can fix better than anyone else. Finally, you should use your knowledge of the industry to make sure you are approaching the issue in the right way.
Explore Pricing Models
SaaS technology offers multiple pricing options that will help you profit from your future product. Defining your monetization strategy is a crucial step of your product development – it directly influences how you’re going to build the app’s functionality and helps you understand how to sell the product after its release. That’s why it’s important to explore the SaaS pricing models and determine which one is best for your solution.
If you’re not sure where to start, it’s always good to look at what the competition’s doing. Once you’ve gone through the pricing models on the market, you can determine what a good starting point is for your business. Remember, however, that growing SaaS companies always test their pricing models. That means you should be willing to alter your pricing to fit your customers’ preferences.
Identify the Product Requirements
The features of your SaaS application represent the central values you provide to end-users. Depending on your niche and pricing model, the app functionality can vary hugely but should, nonetheless, include some core characteristics of a successful SaaS product. Here are some must-have features to incorporate:
High security against vulnerability and hack attacks;
User-friendliness with features like easy navigation and an intuitive UI/UX design;
Real-time support and maintenance so customers can overcome potential challenges;
Although these four steps can help you arrive at a successful SaaS product, it’s important to remember that each component takes time, testing, and refinement. You may even experience overlaps between the steps or complete them in a completely different order.
That is why instead of diving into them directly, you should adapt them to your specific niche and implement them in a way that is efficient for your business. The more you’re ready to test and iterate, the higher your chances of success.
The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.
The most exciting thing about visual search is that it’s becoming a highly accessible way for users to interpret the real world, in real time, as they see it. Rather than being a passive observer, camera phones are now a primary resource for knowledge and understanding in daily life.
Users are searching with their own, unique photos to discover content. This includes interactions with products, brand experiences, stores, and employees, and means that SEO can and should be taken into consideration for a number of real world situations, including:
Though SEOs have little control over which photos people take, we can optimize our brand presentation to ensure we are easily discoverable by visual search tools. By prioritizing the presence of high impact visual search elements and coordinating online SEO with offline branding, businesses of all sizes can see results.
What is visual search?
Sometimes referred to as search-what-you-see, in the context of SEO, visual search is the act of querying a search engine with a photo rather than with text. To surface results , search engines and digital platforms use AI and visual recognition technology to identify elements in the image and supply the user with relevant information.
Though Google’s visual search tools are getting a lot of attention at the moment, they aren’t the only tech team that’s working on visual search. Pinterest has been at the forefront of this space for many years, and today you can see visual search in action on:
In the last year, Google has spoken extensively about their visual search capabilities, hinging a number of their search improvements on Google Lens and adding more and more functionality all the time. As a result, year on year usage of Google Lens has increased by three fold, with an estimated8 billion Google Lens searches taking place each month.
Though there are many lessons to be learned from the wide range of visual search tools, which each have their own data sets, for the purpose of this article we will be looking at visual search on Google Lens and Search.
Are visual search and image search SEO the same?
No, visual search optimization is not exactly the same as image search optimization. Image search optimization forms part of the visual search optimization process, but they’re not interchangeable.
Image search SEO
With Image Search you should prioritize helping images to surface when users enter text based queries. To do this, your images should be using image SEO best practices like:
Modern file formats
Relevant file names
All of this helps Google to return an image search result for a text based query, but one of the main challenges with this approach is that it requires the user to know which term to enter.
For instance, with the query dinosaur with horns, an image search will return a few different dinosaur topic filters and lots of different images. To find the best result, I would need to filter and refine the query significantly.
Visual search SEO
With visual search, the image is the query, meaning that I can take a photo of a toy dinosaur with horns, search with Google Lens, then Google refines the query based on what it can see from the image.
When you compare the two search results, the SERP for the visual search is a better match for the initial image query because there are visual cues within the image. So I am only seeing results for a dinosaur with horns, that is quadrupedal, and only has horns on the face, not the frill.
From a user perspective, this is great because I didn’t have to type anything and I got a helpful result. And from Google’s perspective, this is also more efficient because they can assess the photo and decide which element to filter for first in order to get to the best SERP.
The standard image optimizations form part of what Google considers in order to surface relevant results, but if you stop there, you don’t get the full picture.
Which content elements are best interpreted in visual search
Visual search tools identify objects, text, and images, but certain elements are easier to identify than others. When users carry out a visual search, Google taps into multiple data sources to satisfy the query.
The knowledge graph,Vision AI, Google Maps, and other sources combine to surface search results, but in particular, Google’s tools have a few priority elements. When these elements are present in a photo Google can sort, identify, and/or visually match similar content to return results:
Landmarks are identified visually but are also connected to their physical location on Google Maps, meaning that local businesses or business owners should use imagery to demonstrate their location.
Logos are interpreted in their entirety, rather than as single letters. So even without any text, Google can understand that that swoop means Nike. This data comes from the logos in knowledge panels, website structured data, Google Business Profile, Google Merchant, and other sources, so they should all align.
Knowledge Graph Entities are used to tag and categorize images and have a significant impact on what SERP is displayed for a visual search. Google recognizes around 5 billion KGE, so it is worth considering which ones are most relevant to your brand and ensuring that they are visually represented on your site.
Text is extracted from images via Optical Character Recognition, which has some limitations — not all languages are recognized, nor are backwards letters. So if your users regularly search photos of printed menus or other printed text, you should consider readability of the fonts (or handwriting on specials boards) you use.
Faces are interpreted for sentiment, but the quantity of faces also comes into account, meaning that businesses that serve large groups of people — like event venues or cultural institutions — would do well to include images that demonstrate this.
Visual Search Element
Corresponding Online Activity
Google Business Profile
Website Structured Data
Google Business Profile
Knowledge Graph Entities
Image Structured Data
Google Business Profile
Google Business Profile
Google Business Profile
How to optimize real world spaces for visual search
Just as standard SEO should be focused on meeting and anticipating customer needs, visual search SEO requires awareness of how customers interact with products and services in real world spaces. This means SEOs should apply the same attention to UCG that one would use for keyword research. To that end, I would argue we should also think about consciously applying optimizations to the potential content of these images.
Optimize sponsorship with unobstructed placements
This might seem like a no brainer, but in busy sponsorship spaces it can sometimes be a challenge. As an example, let’s take this photo from a visit to the Staples Center a few years ago.
Like any sports arena, this is filled to the brim with sponsorship endorsements on the court, the basket, and around the venue.
But when I run a visual search assessment for logos, the only one that can clearly be identified is the Kia logo in the jumbotron.
This isn’t because their logo is so distinct or unique, since there is another Kia logo under the basketball hoop, rather this is because the jumbotron placement is clean in terms of composition, with lots of negative space around the logo and fewer identifiable entities in the immediate vicinity.
Within the wider arena, many of the other sponsorship placements are being read as text, including Kia’s logo below the hoop. This has some value for these brands, but since text recognition doesn’t always complete the word, the results can be inconsistent.
So what does any of this have to do with SEO?
Well, Google Image Search now includes results that are using visual recognition, independent of text cues. Meaning that for a Google Image Search for the query kia staples center, two of the top five results do not have the word kia in the copy, alt text, or alt tags of the web pages they are sourced from. So, visual search is impacting rankings here, and with Google Imagesaccounting for roughly 20% of online searches, this can have a significant impact on search visibility.
What steps should you take to SEO your sponsorships?
Whether it’s major league or the local bowling league, in order to get the most benefit from visual search, if you are sponsoring something which is likely to be photographed extensively, you should:
Ensure that your real life sponsorship placement is in an unobscured location
Use the same logo in real life that is in your schema, GBP, and knowledge panel
Get a placement with good lighting and high contrast brand colors
Don’t rely on “light up” logos or flags that have inconsistent visibility on camera phones
You should also ensure that you’re aligning your real life presence with your digital activity. Include images of the sponsorship display on your website so that you can surface for relevant queries. If you dedicate a blog to the sponsorship activity that includes relevant images, image search optimizations, and copy, you increase your chances of outranking other content and bringing those clicks to your site.
Optimizing merch & uniforms for search
When creating merchandising and uniforms, visual discoverability for search should be a priority because users can search photos of promotional merch and images with team members in a number of ways and for an indefinite period of time.
Add text and/or logos
For instance, from my own camera roll, I have a few photos that can be categorized via theGoogle Photo machine-learning-powered image search with the query nasa. Two of these photos include the word “NASA” and the others include the logo.
Oddly enough, though, the photo of my Women of NASA LEGO set does not surface for this query. It shows for lego but not for nasa. Looking closely at the item itself, I can see that neither the NASA logo nor the text have been included in the design of the set.
Adding relevant text and/or logos to this set would have optimized this merchandise for both brands.
Stick to relevant brand colors
And since Google’s visual search AI is also able to discern brand colors, you should also prioritize merchandise that is in keeping with your brand colors. T-shirts and merch that deviate from your core color scheme will be less likely to make Visual Matches when users search via Google Lens.
In the example above, event merchandise that was created outside of the core brand colors of red, black, and white were much less recognizable than stationary typical colors.
Focus on in-person brand experiences
Creating experiences with customers in store and at events can be a great way to build brand relationships. It’s possible to leverage these activities for search if you take an SEO-centric approach.
Let’s consider this image from a promotional experience in Las Vegas for Lyft. As a user, I enjoyed this immensely, so much so that I took a photo.
Though the Viva Lyft Vegas event was created by the rideshare company, in terms of visual search, Pabst are genuinely taking the blue ribbon, as they are the main entity identified in this query. But why?
First, Pabst has claimed their knowledge panel while Lyft has not, meaning that Lyft is less recognizable as a visual entity because it is less defined as an entity.
Second, though it does not have a Google Maps entry, the Las Vegas PBR sign has had landmark-esque treatment since it was installed, with features in The Neon Museum and a UNLV Neon Survey. All of this to say that, in this context, Lyft is being upstaged.
So to create a more SEO-friendly promotional space, they could have laid the groundwork by claiming their knowledge panel and reduced visual search competitors from the viewable space to make sure all eyes were on them.
Encourage optimized use-generated content
Sticking to Las Vegas, here is a typical touristy photo of me with friends outside the Excalibur Hotel:
And when I say that it’s typical, that’s not conjecture. A quick visual search reveals many other social media posts and websites with similar images.
This is what I refer to as that picture. You know the kinds of high occurrence UGC photos: under the castle at the entrance to Disneyland or even thepink wall at Paul Smith’s on Melrose Ave. These are the photos that everyone takes.
Can you SEO these photos for visual search? Yes, I believe you can in two ways:
Encourage people to take photos in certain places that you know, or have designed to include relevant entities, text, logos, and/or landmarks in the viewline. You can do this by declaring an area a scenic viewpoint or creating a photo friendly, dare I say “Instagrammable”, area in your store or venue.
Ensure frequently photographed mobile brand representations (e.g. mascots and/or vehicles) are easily recognizable via visual search. Where applicable, you should also claim their knowledge panels.
Once you’ve taken these steps, create dedicated content on your website with images that can serve as a “visual match” to this high frequency UGC. Include relevant copy and image search optimizations to demonstrate authority and make the most of this visibility.
How does this change SEO?
The notion of bringing visual search considerations to real world spaces may seem initially daunting, but this is also an opportunity for businesses of all sizes to consolidate brand identities in an effective way. Those working in SEO should coordinate efforts with PR, branding, and sponsorship teams to capture visual search traffic for brand wins.
The B2B customer journey can be a long one, especially when the purchase of expensive software subscriptions is under consideration.
“The average B2B customer journey takes 192 days from anonymous first touch to won,” according to Dreamdata in their 2022 B2B Go-to-Market Benchmarks — a statistic described by co-founder and CMO Steffen Hedebrandt as “alarming.”
But the report also indicates that this journey can be significantly sped up — by as much as 63% — if accounts begin their research at software review sites, gathering information and opinions from their peers. Journeys that originate at a review site often lead to deals of higher value too.
Fragmented data on the customer journey. Dreamdata is a B2B go-to-market platform. In any B2B company, explained Hedebrandt, there are typically 10 or even 20 data silos that contain fragments of the customer journey. Website visits, white paper downloads, social media interactions, webinar or meeting attendance, demos, and of course intent data from review site visits — this data doesn’t typically sit in one place within an organization.
“We built an account-based data model because we believe that there’s such a thing as an account journey and not an individual journey,” said Hedebrandt. “So if there are two, three or five people representing an account, which is typically what you see in B2B, all of these touches get mapped into the same timeline.”
Among those many touches is the intent data sourced from software review site G2. Dreamdata has an integration with G2 and a G2 dashboard allowing visualization of G2-generated intent data. This includes filtering prospects who are early in their journey, who have not yet discovered the customer’s product, or who have discovered it but are still searching. This creates a basis for attributing pipelines, conversions and revenue to the activity.
“Strategically, our ideal customer profile is a B2B software-as-a-service company,” said Hedenbrandt. “B2B SaaS companies are particularly ripe for understanding this digital customer journey; their main investment is in digital marketing, they have a salesforce that use software tools to do this inside sales model; and they also deliver their product digitally as well.” What’s more, it takes twice as long to close SaaS deal as it does to close deals with B2B commercial and professional services companies.
The Benchmarks findings. The conclusions of the 2022 Benchmarks report is based on aggregated, anonymized data from more than 400 Dreamdata user accounts. Focusing on first-touch attribution (from their multi-touch model), Dreamdata found that customer journeys where a review site is the first touch are 63% shorter than the average. In contrast, where the first touch channel is social, the journey is much longer than average (217%); it’s the same when paid media is the first touch (155%).
As the Benchmarks report suggests, this may well mean that social is targeting prospects that are just not in-market. It makes sense that activity on a review site is a better predictor of intent.
Hedenbrandt underlines the importance of treating the specific figures with caution. “It’s not complete science what we’ve done,” he admits, “but it’s real data from 400 accounts, so it’s not going to be completely off. You can only spend your time once, and at least from what we can see here it’s better to spend your time collecting reviews than writing another Facebook update.”
While Dreamdata highlights use of G2, Hedenbrandt readily concedes that competitor software review sites might reasonably be expected to show similar effects. “Definitely I would expect it to be similar.”
Why we care. It’s not news that B2B buyers researching software purchases use review sites and that those sites gather and trade in the intent data generated. Software vendors encourage users to post reviews. There has been a general assumption that a large number of hopefully positive reviews is a good thing to have.
Get the daily newsletter digital marketers rely on.
What Dreamdata’s findings indicate is that the effect of review sites on the buyer journey — especially as the first-touch channel — can be quantified and a value placed on it. “None of us questioned the value of reviews, but during this process you can actually map it into a customer journey where you can see the journey started from G2, then flowed into sales meetings, website visits, ads, etc. Then we can also join the deal value to the intent that started from G2.”
Likely, this is also another example of B2B learning from B2C. People looking at high consideration B2C purchases are now accustomed to seeking advice both from friends and from online reviews. The same goes for SaaS purchases, Hedenbrandt suggests: “More people are turning to sites like G2 to understand whether this is a trustworthy vendor or not. The more expensive it is, the more validation you want to see.”
About The Author
Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.
He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.
Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.
Cynthia Ramsaran is director of custom content at Third Door Media, publishers of Search Engine Land and MarTech. A multi-channel storyteller with over two decades of editorial/content marketing experience, Cynthia’s expertise spans the marketing, technology, finance, manufacturing and gaming industries.