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20 Best Tools To Help You Scale

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To grow and succeed in the digital marketplace and increase your team’s content marketing effectiveness, you must build a dependable tech stack that will allow you to grow without placing too much pressure on you or your team.

In this article, we’ll provide ways to boost the efficiency of content marketing strategies and a list of tools to aid you in achieving your objectives together with higher performance.

Strategies for scaling your content marketing efforts

Before we get into the technology you can use to improve your content marketing, let’s look at how you can get better results from developing a successful content team to help improve your performance.

Every team member will have a different job. They will use their respective skills to help the team reach its goals:

Managing editor

This is the person in charge of your content team. They ensure that all the material published is high quality and consistent with the brand’s messaging. Often, their responsibilities include hiring content writers and then collaborating with them to ensure everything is correct and on track.

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SEO analyst

This team member is in charge of ensuring that your website meets SEO standards. They also select the best keywords for each article. SEO analysts help ensure that your material is indexed properly and written with search intent in mind.

Content writer

Most content marketing teams employ in-house writers, outsource the work to independent contractors, or a mixture of both. Because “content” is at the center of all content marketing operations, these individuals are essential for generating high-quality and research-driven material for your blog and other content assets.

Outreach manager

This individual is in charge of sending your material to the appropriate forums on sites where your leads and influencers congregate and creating backlinks so that you receive the most value from each piece of content.

Top tools to grow content marketing and automate workflow

Inefficient workflows can result in delays in the creation of content as well as low-quality content because team members may struggle to work together and communicate effectively. Here are five tools that allow you to take control over the content creation process.

1. Google Docs

Google Docs is a free writing program that permits you to create, edit, and share documents online wherever you are. It is an excellent tool for collaboration and helps your team work together by giving them editing access. Features like “comments,” “suggestions,” and “mentions” let you add relevant information and people to your Docs.

2. GatherContent

GatherContent can be described as a central platform for content creation and collaboration that allows rapid and effective content production.

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The tool offers a medium that lets your team edit and create content, monitor its progress, and publish it when it’s ready. Your team can also create structured content on a large scale in a split second.

3. Narrato

Narrato is a team management system that lets you streamline and control your content creation process, aiding cooperation. The tool has many useful features, including AI assistance, image search, content idea generators, and employee management options. You can organize content using boards, folders, and calendars.

4. Monday.com

It is an “everything you need” platform with collaboration campaign planning and content management tools. The fully customizable templates help your team collaborate, plan, and manage content production more efficiently.

5. Wordable

Wordable allows you to upload Google Docs drafts into WordPress in just minutes and in a designated format. The tool helps keep your documents clean, removing unnecessary spaces and line breaks as well as removing font and span tags.

It also performs other functions such as generating tables automatically, simulating featured images, helping to choose alt text for images, etc.

The best tools for scaling the writing process and optimizing content

Your efforts to market your content depend on your writing skills or search engine optimization strategies. Here are tools that help you improve the writing process and SEO.

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1. WriterAccess

WriterAccess is a platform that connects you with freelancers to create content and streamline your workflow. The Partner AI tools let you research trending topics, find new keywords, optimize content, and track SERPs.

2. Frase

Frase is a tool powered by AI that detects your audience’s questions and assists you in responding to them. It helps your team identify the questions your site visitors would like answered using Google Search. It also creates detailed briefs that allow you to modify your content to meet users’ preferences.

3. MarketMuse

This artificial intelligence-based keyword and content planner allows you to speed up the research process and identify what’s missing from your content compared to your competitors. The tool also helps with content optimization for Google search.

4. Clearscope.io

Clearscope.io makes it possible to discover potential keywords and determine terms you can integrate into your content to optimize it for search engines. The tool is also great for researching content and developing freelancer content briefs.

5. Writesonic

Through Writesonic’s artificial intelligence-powered Writer and Editor, you can write blog posts, articles, essays, e-books, and other types of content at the touch of an icon. Furthermore, you can use our editing tools powered by AI, such as paraphrasers, expanders, and shorteners, to enhance your content.

The most effective methods to increase the reach of content and establish collaborations

Content promotion is an excellent way to connect with the people you want to reach. The following tools will help you connect with your audience and establish collaborations.

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1. Evaboot.com

The most trusted place to find colleagues is LinkedIn. You can pull and search for emails in LinkedIn Sales Navigator with one click using Evaboot.

Evaboot can help you find suitable contacts by scouring the most extensive business network. It achieves this through an extremely effective filter that provides accurate and high-quality results that enable you to connect to skilled people who could help you reach your goals.

2. Respona.com

Respona.com is a link-building software that automates outreach, designs personalized email campaigns, locates emails of individuals you want to contact, and then sends customized pitches to these contacts. Using this tool, it is also possible to build automated sequences of emails you can use to mail personalized proposals to your email list.

3. Mailshake.com

Make your cold outreach fully automated with Mailshake to reach more potential customers and set up more meetings. Mailshake’s email tool utilizes AI and information from thousands of cold email campaigns to create constant, high-quality emails you can send to your leads.

Furthermore, you can use an integrated screen to contact prospects via phone or social media.

4. Hyperise

Hyperise lets you personalize images in your emails, Facebook messaging, chatbots, and LinkedIn. You can customize layers on existing images using Hyperise’s online editor and adjust them instantly on your website.

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5. Icereach

Icereach can reach potential clients through LinkedIn by using intelligent automated sequences. The tool makes it easy to import leads and customize the outreach to a grander scale by adding distinct elements to create an original and customized message. The program will then create an automated drip program with automatic follow-ups.

The most practical tools to improve content distribution

Without an appropriate distribution system that allows you to reach your target audience and display your content quickly, all your efforts will go to the trash even after you’ve created some amazing content. Here are five tools that let you easily publish, share and promote your content.

1. IFTTT

IFTTT is a program that lets you connect to, incorporate, and automate the use of your favorite applications. In integrating with more than 250 personal and business applications, IFTTT is one of the most effective ways to automate your content promotion efforts.

2. Moosend

With its easy-to-use interface, this newsletter tool not just assists you with the design of email drives but also helps you target your list of contacts with specialized content.

3. Planable

You can easily organize your social media posts, collaborate with other users, and plan it from anywhere with Planable. The tool also helps you streamline your social media publishing process by letting you schedule your posts.

4. Quuu

Quuu is software that can help you get top-quality suggestions according to your target audience’s interests. Quuu’s proprietary artificial intelligence algorithm will identify high-quality content and send it to your third-party scheduling tool. It is one of the best tools to automate your social media marketing!

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5. Outbrain.com

Outbrain provides marketers with customized recommendations for the top magazines in the world to reach their targeted audience. Its proprietary algorithms help capture your audience’s attention and guide them into taking action.

Wrapping up

Content marketing is the best way to establish the credibility of your brand and expand your enterprise. The tools listed in this guide can be utilized to create a distribution plan, measure your marketing effectiveness, and even make your customers feel more involved, assisting you in improving your company’s performance.

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The Current State of Google’s Search Generative Experience [What It Means for SEO in 2024]

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The Current State of Google's Search Generative Experience [What It Means for SEO in 2024]

SEO enthusiasts, known for naming algorithm updates after animals and embracing melodrama, find themselves in a landscape where the “adapt or die” mantra prevails. So when Google announced the launch of its Search Generative Experience (SGE) in May of 2023 at Google/IO, you can imagine the reaction was immense.

Although SGE has the potential to be a truly transformative force in the landscape, we’re still waiting for SGE to move out of the Google Labs Sandbox and integrate into standard search results. 

Curious about our current take on SGE and its potential impact on SEO in the future? Read on for more.

Decoding Google’s Defensive Move

In response to potential threats from competitors like ChatGPT, Bing, TikTok, Reddit, and Amazon, Google introduced SGE as a defensive maneuver. However, its initial beta release raised questions about its readiness and global deployment.

ChatGPT provided an existential threat that had the potential to eat into Google’s market share. When Bing started incorporating it into its search results, it was one of the most significant wins for Bing in a decade. In combination with threats from TikTok, Reddit, and Amazon, we see a more fractured search landscape less dominated by Google. Upon its launch, the expectation was that Google would push its SGE solution globally, impact most queries, and massively shake up organic search results and strategies to improve organic visibility.

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Now, industry leaders are starting to question if Google is better off leaving SGE in the testing ground in Google labs. According to Google’s recent update, it appears that SGE will remain an opt-in experience in Google Labs (for at least the short term). If SGE was released, there could be a fundamental reset in understanding SEO. Everything from organic traffic to optimization tactics to tracking tools would need adjustments for the new experience. Therefore, the prospect of SGE staying in Google Labs is comforting if not entirely reliable. 

The ever-present option is that Google can change its mind at any point and push SGE out broadly as part of its standard search experience. For this reason, we see value in learning from our observations with SGE and continuing to stay on top of the experience.

SGE User Experience and Operational Challenges

If you’ve signed up for search labs and have been experimenting with SGE for a while, you know firsthand there are various issues that Google should address before rolling it out broadly to the public.

At a high level, these issues fall into two broad categories including user experience issues and operational issues.

Below are some significant issues we’ve come across, with Google making notable progress in addressing certain ones, while others still require improvement:

  • Load time – Too many AI-generated answers take longer to load than a user is willing to wait. Google recommends less than a 3-second load time to meet expectations. They’ll need to figure out how to consistently return results quickly if they want to see a higher adoption rate.
  • Layout – The SGE layout is massive. We believe any major rollout will be more streamlined to make it a less intrusive experience for users and allow more visibility for ads, and if we’re lucky, organic results. Unfortunately, there is still a decent chance that organic results will move below the fold, especially on mobile devices. Recently, Google has incorporated more results where users are prompted to generate the AI result if they’d like to see it. The hope is Google makes this the default in the event of a broad rollout where users can generate an AI result if they want one instead of assuming that’s what a user would like to see. 
  • Redundancy – The AI result duplicates features from the map pack and quick answer results. 
  • Attribution – Due to user feedback, Google includes sources on several of their AI-powered overviews where you can see relevant web pages if there is an arrow next to the result. Currently, the best way to appear as one of these relevant pages is to be one of the top-ranked results, which is convenient from an optimization standpoint. Changes to how attribution and sourcing are handled could heavily impact organic strategies. 

 

On the operational side, Google also faces significant hurdles to making SGE a viable product for its traditional search product. The biggest obstacle appears to be making the cost associated with the technology worth the business outcomes it provides. If this was a necessary investment to maintain market share, Google might be willing to eat the cost, but if their current position is relatively stable, Google doesn’t have much of an incentive to take on the additional cost burden of heavily leveraging generative AI while also presumably taking a hit to their ad revenue. Especially since slow user adoption doesn’t indicate this is something users are demanding at the moment.

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While the current experience of SGE is including ads above the generative results now, the earliest iterations didn’t heavily feature sponsored ads. While they are now included, the current SGE layout would still significantly disrupt the ad experience we’re used to. During the Google I/O announcement, they made a statement to reassure advertisers they would be mindful of maintaining a distinct ad experience in search.  

“In this new generative experience, Search ads will continue to appear in dedicated ad slots throughout the page. And we’ll continue to uphold our commitment to ads transparency and making sure ads are distinguishable from organic search results” – Elizabeth Reid, VP, Search at Google

Google is trying to thread a delicate needle here of staying on the cutting edge with their search features, while trying not to upset their advertisers and needlessly hinder their own revenue stream. Roger Montti details more of the operational issues in a recent article digging into the surprising reasons SGE is stuck in Google Labs.

He lists three big problems that need to be solved before SGE will be integrated into the foreground of search:

  1. Large Language Models being inadequate as an information retrieval system
  2. The inefficiency and cost of transformer architecture
  3. Hallucinating (providing inaccurate answers)

 

Until SGE provides more user value and checks more boxes on the business sense side, the traditional search experience is here to stay. Unfortunately, we don’t know when or if Google will ever feel confident they’ve addressed all of these concerns, so we’ll need to stay prepared for change.

Experts Chime in on Search Generative Experience

Our team has been actively engaging with SGE, here’s a closer look at their thoughts and opinions on the experience so far:

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“With SGE still in its early stages, I’ve noticed consistent changes in how the generative results are produced and weaved naturally into the SERPs. Because of this, I feel it is imperative to stay on top of these on-going changes to ensure we can continue to educate our clients on what to expect when SGE is officially incorporated into our everyday lives. Although an official launch date is currently unknown, I believe proactively testing various prompt types and recording our learnings is important to prepare our clients for this next evolution of Google search.” – Jon Pagano, SEO Sr. Specialist at Tinuiti

“It’s been exciting to watch SGE grow through different variations over the last year, but like other AI solutions its potential still outweighs its functionality and usefulness. What’s interesting to see is that SGE doesn’t just cite its sources of information, but also provides an enhanced preview of each webpage referenced. This presents a unique organic opportunity where previously untouchable top 10 rankings are far more accessible to the average website. Time will tell what the top ranking factors for SGE are, but verifiable content with strong E-E-A-T signals will be imperative. –Kate Fischer, SEO Specialist at Tinuiti

“Traditionally, AI tools were very good at analytical tasks. With the rise of ChatGPT, users can have long-form, multi-question conversations not yet available in search results. When, not if, released, Google’s Generative Experience will transform how we view AI and search. Because there are so many unknowns, some of the most impactful ways we prepare our clients are to discover and develop SEO strategies that AI tools can’t directly disrupt, like mid to low funnel content.” – Brandon Miller, SEO Specialist at Tinuiti

“SGE is going to make a huge impact on the ecommerce industry by changing the way users interact with the search results. Improved shopping experience will allow users to compare products, price match, and read reviews in order to make it quicker and easier for a user to find the best deals and purchase. Although this leads to more competitive results, it also improves organic visibility and expands our product reach. It is more important than ever to ensure all elements of a page are uniquely and specifically optimized for search. With the SGE updates expected to continue to impact search results, the best way to stay ahead is by focusing on strong user focused content and detailed product page optimizations.”  – Kellie Daley, SEO Sr. Specialist at Tinuiti

Navigating the Clash of Trends

One of the most interesting aspects of the generative AI trend in search is that it appears to be in direct opposition to other recent trends.

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One of the ways Google has historically evaluated the efficacy of its search ranking systems is through the manual review of quality raters. In their quality rater guidelines, raters were instructed to review for things like expertise, authority, and trustworthiness (EAT) in results to determine if Google results are providing users the information they deserve. 

In 2022, Google updated their search guidelines to include another ‘e’ in the form of experience (EEAT). In their words, Google wanted to better assess if the content a user was consuming was created by someone with, “a degree of experience, such as with actual use of a product, having actually visited a place or communicating what a person has experienced. There are some situations where really what you value most is content produced by someone who has firsthand, life experience on the topic at hand.” 

Generative AI results, while cutting-edge technology and wildly impressive in some cases, stand in direct opposition to the principles of E-E-A-T. That’s not to say that there’s no room for both in search, but Google will have to determine what it thinks users value more between these competing trends. The slow adoption of SGE could be an indication that a preference for human experience, expertise, authority, and trust is winning round one in this fight. 

Along these lines, Google is also diversifying its search results to cater to the format in which users get their information. This takes the form of their Perspectives Filter. Also announced at Google I/O 2023, the perspectives filter incorporates more video, image, and discussion board posts from places like TikTok, YouTube, Reddit, and Quora. Once again, this trend shows the emphasis and value searchers place on experience and perspective. Users value individual experience over the impersonal conveyance of information. AI will never have these two things, even if it can provide a convincing imitation.

The current iteration of SGE seems to go too far in dismissing these trends in favor of generative AI. It’s an interesting challenge Google faces. If they don’t determine the prevailing trend correctly, veering too far in one direction can push more market share to ChatGPT or platforms like YouTube and TikTok.

Final Thoughts

The range of outcomes remains broad and fascinating for SGE. We can see this developing in different ways, and prognostication offers little value, but it’s invaluable to know the potential outcomes and prepare for as many of them as possible.

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It’s critical that you or your search agency be interacting and experimenting with SGE because:

  • The format and results will most likely continue to see significant changes
  • This space moves quickly and it’s easy to fall behind
  • Google may fix all of the issues with SGE and decide to push it live, changing the landscape of search overnight
  • SGE experiments could inform other AI elements incorporated into the search experience

 

Ultimately, optimizing for the specific SGE experience we see now is less important because we know it will inevitably continue changing. We see more value in recognizing the trends and problems Google is trying to solve with this technology. With how quickly this space moves, any specifics mentioned in this article could be outdated in a week. That’s why focusing on intention and process is important at this stage of the game.

By understanding the future needs and wants SGE is attempting to address, we can help you future-proof your search strategies as much as possible. To some extent we’re always at the whims of the algorithm, but by maintaining a user-centric approach, you can make your customers happy, regardless of how they find you.

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Here’s Optimizely’s Automatic Sample Ratio Mismatch Detection

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Here's Optimizely’s Automatic Sample Ratio Mismatch Detection

Optimizely Experiment’s automatic sample ratio mismatch (SRM) detection delivers peace of mind to experimenters. It reduces a user’s exposure time to bad experiences by rapidly detecting any experiment deterioration.

This deterioration is caused by unexpected imbalances of visitors to a variation in an experiment. Most importantly, this auto SRM detection empowers product managers, marketers, engineers, and experimentation teams to confidently launch more experiments. 

How Optimizely Experiment’s stats engine and automatic sample rate mismatch detection work together

The sample ratio mismatch actslike the bouncer at the door who has a mechanical counter, checking guests’ tickets (users) and telling them which room they get to party in.

Stats engine is like the party host who is always checking the vibes (behavior) of the guests as people come into the room.

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If SRM does its job right, then stats engine can confidently tell which party room is better and direct more traffic to the winning variation (the better party) sooner.

Why would I want Optimizely Experiment’s SRM detection?

It’s equally important to ensure Optimizely Experiment users know their experiment results are trustworthy and have the tools to understand what an imbalance can mean for their results and how to prevent it.

Uniquely, Optimizely Experiment goes further by combining the power of automatic visitor imbalance detection with an insightful experiment health indicator. This experiment health indicator plays double duty by letting our customers know when all is well and there is no imbalance present.

Then, when just-in-time insight is needed to protect your business decisions, Optimizely also delivers just-in-time alerts that help our customers recognize the severity of, diagnose, and recover from errors.

Why should I care about sample ratio mismatch (SRM)?

Just like a fever is a symptom of many illnesses, a SRM is a symptom of a variety of data quality issues. Ignoring a SRM without knowing the root cause may result in a bad feature appearing to be good and being shipped out to users, or vice versa. Finding an experiment with an unknown source of traffic imbalance lets you turn it off quickly and reduce the blast radius.

Then what is the connection between a “mismatch” and “sample ratio”?

When we get ready to launch an experiment, we assign a traffic split of users for Optimizely Experiment to distribute to each variation. We expect the assigned traffic split to reasonably match up with the actual traffic split in a live experiment. An experiment is exposed to an SRM imbalance when there is a statistically significant difference between the expected and the actual assigned traffic splits of visitors to an experiment’s variations.

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1. A mismatch doesn’t mean an imperfect match

Remember: A bonified imbalance requires a statistically significant result of the difference in visitors. Don’t expect a picture-perfect, identical, exact match of the launch-day traffic split to your in-production traffic split. There will always be some ever-so-slight deviation.

Not every traffic disparity automatically signifies that an experiment is useless. Because Optimizely deeply values our customers’ time and energy, we developed a new statistical test that continuously monitors experiment results and detects harmful SRMs as early as possible. All while still controlling for crying wolf over false positives (AKA when we conclude there is a surprising difference between a test variation and the baseline when there is no real difference). 

2. Going under the hood of Optimizely Experiment’s SRM detection algorithm

Optimizely Experiment’s automatic SRM detection feature employs a sequential Bayesian multinomial test (say that 5 times fast!), named sequential sample ratio mismatch. Optimizely statisticians Michael Lindon and Alen Malek pioneered this method, and it is a new contribution to the field of Sequential Statistics. Optimizely Experiment’s sample ratio mismatch detection harmonizes sequential and Bayesian methodologies by continuously checking traffic counts and testing for any significant imbalance in a variation’s visitor counts. The algorithm’s construction is Bayesian inspired to account for an experiment’s optional stopping and continuation while delivering sequential guarantees of Type-I error probabilities.

3. Beware of chi-eap alternatives!

The most popular freely available SRM calculators employ the chi-square test. We highly recommend a careful review of the mechanics of chi-square testing. The main issue with the chi-squared method is that problems are discovered only after collecting all the data. This is arguably far too late and goes against why most clients want SRM detention in the first place. In our blog post “A better way to test for sample ratio mismatches (or why I don’t use a chi-squared test)”, we go deeper into chi-square mechanics and how what we built accounts for the gaps left behind by the alternatives.

Common causes of an SRM  

1. Redirects & Delays

A SRM usually results from some visitors closing out and leaving the page before the redirect finishes executing. Because we only send the decision events once they arrive on the page and Optimizely Experiment loads, we can’t count these visitors in our results page unless they return at some point and send an event to Optimizely Experiment.

A SRM can emerge in the case of anything that would cause Optimizely Experiment’s event calls to delay or not fire, such as variation code changes. It also occurs when redirect experiments shuttle visitors to a different domain. This occurrence is exacerbated by slow connection times.

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2. Force-bucketing

If a user first gets bucketed in the experiment and then that decision is used to force-bucket them in a subsequent experiment, then the results of that subsequent experiment will become imbalanced.

Here’s an example:

Variation A provides a wildly different user experience than Variation B.

Visitors bucketed into Variation A have a great experience, and many of them continue to log in and land into the subsequent experiment where they’re force-bucketed into Variation A.

But, visitors who were bucketed into Variation B aren’t having a good experience. Only a few users log in and land into a subsequent experiment where they will be force-bucketed into Variation B.

Well, now you have many more visitors in Variation A than in Variation B.

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3. Site has its own redirects

Some sites have their own redirects (for example, 301s) that, combined with our redirects, can result in a visitor landing on a page without the snippet. This causes pending decision events to get locked in localStorage and Optimizely Experiment never receives or counts them.

4. Hold/send events API calls are housed outside of the snippet

Some users include hold/send events in project JS. However, others include it in other scripts on the page, such as in vendor bundles or analytics tracking scripts. This represents another script that must be properly loaded for the decisions to fire appropriately. Implementation or loading rates may differ across variations, particularly in the case of redirects.

Interested?  

If you’re already an Optimizely Experiment customer and you’d like to learn more about how automatic SRM detection benefits your A/B tests, check out our knowledge base documentation:

For further details you can always reach out to your customer success manager but do take a moment to review our documentation first!

If you’re not a customer, get started with us here! 

And if you’d like to dig deeper into the engine that powers Optimizely experimentation, you can check out our page faster decisions you can trust for digital experimentation. 

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How to Use Email Marketing Automation to Encourage SaaS Adoption

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How to Use Email Marketing Automation to Encourage SaaS Adoption

SaaS adoption refers to the process that earns your product a permanent place in your user’s workflow. This happens when you empower your audience to extract useful value from your solutions.

Email, a tried and tested communication tool, plays an essential role in helping brands relay their product’s value to their customers and educate them on how to make the most of it.

However, smaller teams might find themselves at a crossroads, balancing the need for personalized communication with the scale of their user base

Email marketing automation offers a practical solution by ensuring that each message is tailored and timely, yet sent out with minimal manual effort.

In this article, let’s look at five tips that will help you build robust email marketing automation that will motivate your audience to adopt your tool and make it a part of their daily lives.

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1. Segment your audience

Audience segmentation is crucial for personalizing your emails, which in turn, can significantly boost SaaS product adoption. Remember, a message that resonates with one segment might not strike a chord with another.

The key to effective segmentation is understanding where each customer is in their journey. Are they new subscribers, active users, or perhaps at the brink of churning?

Here are some actionable steps to segment your audience effectively:

  1.  Analyze User Behavior: Look at how different users interact with your SaaS product. Are they frequent users, or do they log in sporadically? This insight can help you create segments like ‘active users’, ‘occasional users’, and ‘at-risk users’.
  2.  Utilize Sign-up Data: Leverage the information gathered during the sign-up process. This can include job roles, company size, or industry, which are excellent parameters for segmentation.
  3.  Monitor Engagement Levels: Keep an eye on how different segments interact with your emails. Are they opening, clicking, or ignoring your messages? This feedback will help you refine your segments and tailor your approach. Plus, consider setting up small business phone systems to enhance communication with your audience.

2. Create campaigns based on behavior

Sending behavior-based campaigns is pivotal in effective email marketing. By focusing on performance metrics such as open rates, click-through rates, and engagement times, you can gauge the effectiveness of your emails and adjust your strategy accordingly.

You can also use digital signage to entertain or make customers aware of something new – product or service, through a digital sign.

Different types of email campaigns serve various purposes:

  1. Educational Campaigns: These are designed to inform and enlighten your audience about their problem. They can include tips, best practices, and how-to guides. The goal here is to provide value and establish your brand as a thought leader in your industry.
  2. Interactive Campaigns: These campaigns encourage user engagement through surveys, quizzes, microblogging platforms, or feedback forms. They not only provide valuable insights into user preferences but also make the recipients feel heard and valued.
  3. Onboarding Campaigns: Targeted toward new users, these messages help them get the value they seek from your product as soon as possible. They can include step-by-step tutorials, video guides, or links to helpful resources.

4.Re-engagement Campaigns: Aimed at inactive users, these emails strive to reignite their interest in your SaaS product. They might include product updates, special offers, or reminders of the benefits they’re missing out on.

3. A/B test before deployment

Rather than pushing a new campaign to your entire audience as soon as you draft the emails, A/B testing helps you know whether your messages are any good.

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Here are some best practices for A/B testing in email automation:

  1. Test One Variable at a Time: Whether it’s the subject line, email content, or call-to-action, change just one (or a couple) element per test. This clarity helps in pinpointing exactly what works and what doesn’t.
  2. Choose a Representative Sample: Ensure that the test group is a good mix of your target audience as a whole. This way, the results are more likely to reflect how your entire audience would react.
  3. Measure the Right Metrics: Depending on what you’re testing, focus on relevant metrics like open rates, click-through rates, or conversion rates. This will give you a clear picture of the impact of your changes. Along with these steps, it’s important to use an SPF checker to ensure your emails aren’t marked as spam and increase the deliverability rate.
  4. Use the Results to Inform Your Strategy: Once you have the results, don’t just stop at implementing the winning version. Analyze why it performed better and use these insights to inform your future campaigns.
  5. Don’t Rush the Process: Give your test enough time to gather significant data. Adopt comprehensive marketing reporting solutions that give you a clear picture of your campaigns’ efficacy.

4. Leverage email templates

When managing multiple email automation campaigns, each with potentially dozens of emails, the task of creating each one from scratch can be daunting. Not to mention, if you have multiple writers on board, there’s a risk of inconsistency in tone, style, and branding.

Email templates are your secret weapon for maintaining consistency and saving time. They provide a standardized framework that can be easily customized for different campaigns and purposes.

They are also a great way to communicate with your customers. Another way to communicate efficiently with your customer is through best small business phone systems, which is especially efficient when conveying information about your product or service.

Here’s a rundown of various types of templates you should consider having:

  1. Welcome: For greeting new subscribers or users. It should be warm, inviting, and informative, setting the tone for future communications.
  2. Educational Content: Used for sharing tips, guides, and resources. If you are making this template to introduce online GCSE physics tutor services that you provide, you should be clear, concise, and focused on delivering value in your template.
  3. Promotional: For announcing new features, offers, or services. It should be eye-catching and persuasive without being overly salesy.
  4. Feedback Request: Designed to solicit user feedback. This template should be engaging and make it easy for recipients to respond.
  5. Re-engagement: Aimed at rekindling interest among inactive users. It should be attention-grabbing and remind them of what they’re missing.
  6. Event Invitation: For webinars, workshops, or other events. This should be exciting and informative, providing all the necessary details.

5. Use a tool that works for you

Email is more than just a marketing platform; it’s a multifaceted tool that can drive customer engagement, support, and retention. Given its versatility, it’s crucial to choose the right email automation tool that aligns with your specific needs.

When selecting an email automation tool, consider these key features:

  1. Intuitive Interface: Even your non-technical team members should find it easy to use.
  2. Robust Segmentation Capabilities: The tool must offer advanced segmentation options to target your emails accurately.
  3. A/B Testing Functionality: Essential for optimizing your email campaigns.
  4. Integration with Other Tools: Look for a tool that integrates seamlessly with your CRM, analytics, and other marketing platforms. Additionally, integrating a multilingual translation support can further enhance the tool’s versatility, allowing you to reach a diverse audience with tailored content in their preferred languages.

Popular tools like Mailchimp and ActiveCampaign offer free trials which are great for brands to take these for a spin before making a choice.

Wrapping up

Leveraging email automation makes it easier for SaaS brands to market their solutions to their audience and ultimately increase adoption rates.

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Segmenting audiences, creating messages based on their behavior, testing emails before setting campaigns live, utilizing templates for speed and consistency, and adopting a tool that you are comfortable working with are essential email marketing automation tips to help you get started on the right foot.

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