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Six data-driven SEO strategies that optimize conversion rates

February 22, 2022 No Comments

Six data-driven SEO strategies that optimize conversion rates

30-second summary:

  • Since Google now focuses heavily on user experience, using data as a pillar to uncover consumer insights will drive your digital marketing success
  • However, marketing teams still need to understand these sources and their areas of impact on the consumer’s experience
  • Atul Jindal helps you cover the ground with his advice and case studies

Studies have shown that businesses using data-driven strategies experience five to eight times higher ROI. Conversion rate optimization (CRO) is a process that largely depends on data. The core focus for most CRO strategies is to use consumer data to make their customer journey smoother and experience better.

With search engines also increasing emphasis on user experience, we find a point where SEO strategies start to complement CRO strategies.

But your SEO tactics can truly augment your CRO efforts when driven by data.

In this article, I share six data-driven SEO strategies to supplement your CRO efforts.

From content audit to website personalization, read till the end to find out how you can boost your search engine rankings and conversions altogether!

Data-driven SEO strategies to supplement CRO

Data-driven strategies are online marketing tactics fueled by consumer data. Unlike traditional marketing strategies, data-driven strategies are based on data-backed hypotheses rather than assumptions.

This reliance on solid data makes such strategies the star of the modern marketing world.

Here are six data-driven SEO strategies to make your CRO efforts more promising:

1. Website analysis and optimization

Website analysis is a process through which you test various elements of your website. It analyzes the overall performance of your website and highlights areas of improvement.

The elements that web analysis takes into account include the website’s on-page optimization and technical SEO, finding out about the keywords it ranks for, and what rank it has for different keywords.

Using various web analytics tools, this process also uncovers sources where your website gets traffic from, highlights the flaws in your website’s usability and UX, and provides the basis for the website’s load speed optimization.

Through all of these elements, it helps in enhancing your website’s overall user experience and contributes towards conversion rate optimization.

Additionally, it also provides your web traffic’s demographic and interest data, enabling you to optimize the website for a more relevant user experience.

Google Analytics is the most comprehensive and reliable tool to support your website analysis and optimization efforts. It integrates with your website and tracks all the data you need to optimize your website for an enhanced user experience.

A leading marketing automation software company experienced 10x higher conversion rates when they integrated their native real-time personalization tool with Google Analytics to use the personalization data. This was paired with the Google Analytics information to serve personalized remarketing ads through Google AdWords.

Not only did they experience higher conversion rates, but with the effective use of web analytics data, like demographic and behavior information, they also experienced a 107 percent YoY increase in qualified leads.

2. Content analysis and optimization

Content analysis is similar to website analysis, but instead of testing your website’s technical elements, it analyzes your website’s content and overall content strategy to uncover areas of improvement.

Conversion rates are almost six times higher for businesses that invest in content marketing. But results like this manifest only when your website brims with optimized content.

The purpose of your content is to compel users to take the desired action, or in other words, convert.

Content analysis finds out how well it serves this purpose.

You can uncover various metrics with content analysis, like which content type is the most popular among your audience, which content is bringing you closer to your marketing objectives, and which needs more work.

For example, a marketing optimization software company may have blogs and case studies in its content strategy. Their web analytics may reveal that case studies drive more conversions while blogs get the most social shares.

With its content marketing objective being increased conversions, content analysis will help them focus more on publishing more case studies.

An effective content analysis will also uncover whether or not your content matches the search intent of your target search queries. And therefore, whether or not you need to find new SEO keywords and re-optimize. If your content doesn’t match the search intent perfectly, even if it gets traffic, those users will not convert.

So, in essence, content analysis will help increase conversions by helping you create content that is proven to drive results. It will also help save time and resources from being spent on less-profitable strategies.

Here’s a case study discussing how changing content on your website can reflect a spike in revenue.

Brookdaleliving.com, a website offering community living solutions for the elderly, had a disappointing website conversion rate. But then, their website had nothing that would drive conversions.

The digital marketing experts they hired revamped their website and tested two different content types on their landing page – an image and a testimonial video – to see which one performs better.

Ironically, the web page with an image drove 3.92 percent higher conversions than the original page. This may seem like a small increment, but it resulted in additional revenue of $ 106,000.

3. Website design optimization

Tests like usability testing and A/B testing provide the data that drives website design optimization to improve a website’s design and enhance its user experience.

The purpose of CRO is to make the user journey smoother and experience better.

Website design optimization supports CRO by removing frictions in the buyer’s journey and making it easier for them to accomplish their goals.

But there are a couple of best practices the website design must adhere to to ensure that it really contributes to your CRO efforts.

  1. The design should be simple and somewhat similar to what the users are accustomed to
  2. The navigation bar should be designed intuitively, with the user’s search intent in mind, so they can quickly find what they came looking for
  3. The content arrangement should follow proven design techniques that enhance content readability and value delivery

For your web design to truly serve your business, you will have to continue to test various combinations of website elements, their placements, and designs.

Regardless of how you go about your web design, making the target audience’s journey easier should be at the heart of all your efforts.

Trucker Reports, a trucker’s community that helps truck drivers find jobs, struggled with low conversions.

The CRO experts they hired performed a web design audit and discovered multiple opportunities. Based on these opportunities, they tested different hypotheses.

They tested three different designs against the original ones in their final test and found out that the final design had 79.3 percent higher conversions.

Do you know why?

Because this last design had the least friction and made it easier for the users to convert.

4. Audience analysis

Audience analysis, commonly known as audience research, is the process through which you dig up information about your prospects so you can develop targeted marketing campaigns.

Since user experience is a massive part of SEO and CRO alike, audience analysis holds an important place as a data-driven SEO strategy for conversion rate optimization.

This process uncovers a wide variety of data, from core demographic information like age, gender, marital status, income, education, etc., to online behavior, internal and external challenges, and more.

Audience analysis helps develop a buyer persona, which then becomes the foundation of a highly-targeted marketing campaign.

Audience analysis is a core element of a successful CRO campaign because it makes your website relevant to the users. You find out about their pain points and struggles and are better equipped to address them through your content.

This shows that you care about your customers and inevitably builds trust between your brand and its prospects. Given that the modern customer prioritizes their connection with the brand when making purchase decisions, this bond of trust and reliability results in higher conversions.

Data-backed audience analysis also allows you to segment your audience based on their demographic information and interest. With this level of segmentation, you spend your efforts and resources on people you know matter to your business.

This is why studies indicate a 56 percent reduction in marketing costs for businesses that use audience analysis as a basis for all their marketing efforts.

5. Testing and optimization

Testing is the life of conversion rate optimization. You put samples of your content and design arrangements to test to see which one performs better and optimize using the results of these tests.

These tests are all data-driven, that is, they are based on hypotheses generated from existing data and provide insights into how valid the hypothesis is.

For example, data may show a higher conversion rate on websites with explainer videos. This forms the hypothesis of your test. So, you develop two different landing pages, one with a video and another with an image, to see which performs better. If the videos result in higher conversions, you know what to continue optimizing with!

You can perform different kinds of tests when optimizing websites for conversions. Two of the popular ones include usability testing and A/B or split testing.

Search engines also recommend A/B and multivariate testing for SEO as it improves user experience, which search engines pursue in the websites they index.  

NatureAir performed A/B testing on their landing page to increase conversions. One of the samples had a CTA on the side, while the other had a CTA prominently placed in the content area.

Once the test results were in, they found that placing CTA in the content area increases conversions by 591 percent!

That’s how potent A/B tests can be!

6. Website personalization

According to Google, 90 percent of marketers believe personalization results in business profitability. And why shouldn’t it? In an era with so many similar websites, a web page that offers a customized experience deserves to make better revenue.

Website personalization is a relatively complex process through which you can serve a unique experience to each visitor. These experiences are designed based on consumer data, including their demographic data, interests, search history, and online behavior.

75 percent of consumers prefer that online sellers use personal information to enhance shopping experiences.

People want you to make shopping easier for them, adding a personalized product recommendation on your website will help improve your user experience and could boost sales. They don’t want to go out and search for what they want. They want you to know what they need and bring it to them. And that’s what website personalization empowers you to do.

It improves overall website experience, lowers bounce rates, boosts SEO, and of course, increases conversions.

Serving dynamic content makes the customer’s experience more intuitive and relevant. It lets you put out the content that interests them the most, and hence, contributes to better revenue.

Conclusion

The goal of an SEO and a CRO campaign have become somewhat similar ever since search engines have started giving value to user experience.

There are many SEO strategies focused on improving UX. And these strategies, when backed by data, can lead to increased conversion rates.

Therefore, I have discussed some of the most promising data-driven SEO strategies that can drive conversions in this article.

But the true results of a strategy depend on how well you implement it. So, ramp up your data analysis game, derive insights, implement them, and optimize your strategies for better results.


Atul Jindal is a web design and marketing specialist, having interests in doing websites/apps optimized for SEO with a core focus on conversion optimization. He creates web experiences that bring conversations and transform web traffic into paying customers or leads.

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Transposit scores $35M to build data-driven runbooks for faster disaster recovery

September 7, 2020 No Comments

Transposit is a company built by engineers to help engineers, and one big way to help them is to get systems up and running faster when things go wrong — as they always will at some point. Transposit has come up with a way to build runbooks for faster disaster recovery, while using data to update them in an automated fashion.

Today, the company announced a $ 35 million Series B investment led by Altimeter Capital, with participation from existing investors Sutter Hill Ventures, SignalFire and Unusual Ventures. Today’s investment brings the total raised to $ 50.4 million, according to the company.

Company CEO Divanny Lamas and CTO and founder Tina Huang see technology issues as less an engineering problem and more as a human problem, because it’s humans who have to clean up the messes when things go wrong. Huang says forgetting the human side of things is where she thinks technology has gone astray.

“We know that the real superpower of the product is that we focus on the human and the user side of things. And as a result, we’re building an engineering culture that I think is somewhat differentiated,” Huang told TechCrunch.

Transposit is a platform that at its core helps manage APIs, connections to other programs, so it starts with a basic understanding of how various underlying technologies work together inside a company. This is essential for a tool that is trying to help engineers in a moment of panic figure out how to get back to a working state.

When it comes to disaster recovery, there are essentially two pieces: getting the systems working again, then figuring out what happened. For the first piece, the company is building data-driven runbooks. By being data-driven, they aren’t static documents. Instead, the underlying machine learning algorithms can look at how the engineers recovered and adjust accordingly.

Transposit diaster recovery dashboard

Image Credits: Transposit

“We realized that no one was focusing on what we realize is the root problem here, which is how do I have access to the right set of data to make it easier to reconstruct that timeline, and understand what happened? We took those two pieces together, this notion that runbooks are a critical piece of how you spread knowledge and spread process, and this other piece, which is the data, is critical,” Huang said.

Today the company has 26 employees, including Huang and Lamas, who Huang brought on board from Splunk last year to be CEO. The company is somewhat unique having two women running the organization, and they are trying to build a diverse workforce as they build their company to 50 people in the next 12 months.

The current make-up is 47% female engineers, and the goal is to remain diverse as they build the company, something that Lamas admits is challenging to do. “I wish I had a magic answer, or that Tina had a magic answer. The reality is that we’re just very demanding on recruiters. And we are very insistent that we have a diverse pipeline of candidates, and are constantly looking at our numbers and looking at how we’re doing,” Lamas said.

She says being diverse actually makes it easier to recruit good candidates. “People want to work at diverse companies. And so it gives us a real edge from a kind of culture perspective, and we find that we get really amazing candidates that are just tired of the status quo. They’re tired of the old way of doing things and they want to work in a company that reflects the world that they want to live in,” she said.

The company, which launched in 2016, took a few years to build the first piece, the underlying API platform. This year it added the disaster recovery piece on top of that platform, and has been running its beta since the beginning of the summer. They hope to add additional beta customers before making it generally available later this year.


Enterprise – TechCrunch


Digital marketing during COVID-19 times: Data-driven insights

June 11, 2020 No Comments

30-second summary:

  • More than 4500 digital marketing professionals from the USA and Europe participated in the anonymous survey. We asked them about the impact of COVID-19 on their business and the working routine.
  • 63% of participants reallocate budgets to activities that bring results in the short term.
  • Most entrepreneurs in the internet marketing believe that it is necessary to adapt as much as possible to new conditions not to lose current customers and quickly return to pre-quarantined indicators.
  • Some respondents talk about increasing the volume of work and improving business indicators: 18% of respondents noted an increase in sales, 27% reported an increase in traffic, and 12% received new customers.

We can see and feel the impact of COVID-19 on a company of any size. By now, many have refactored their business logic by cutting expenses as much as practical, offering contactless delivery options or curbside pickup, etc. Internet marketing transformation is another key point in the list of business alterations.

In this article, we’ll share the results of Serpstat’s research on the effects of quarantine on digital marketing. Read on to keep your businesses ahead of the curve and adapt your strategic planning.

About the study

More than 4,500 respondents from the USA, Germany, Spain, and other European states participated in the anonymous survey. They were Serpstat platform users, which includes, digital marketing professionals that work for or run small or medium-sized businesses, agencies, or teams. Niche freelancers were also among the respondents.

The strategic aim of the Serpstat research was to use a numbers-driven approach and highlight insights that go beyond subjectivity.

Survey highlights reel

 Here are the key results of the research:

  • In 60% of companies, no employees were dismissed from their positions. What is more, there were no such plans in the roadmap. Meanwhile, 24% of the survey participants confirmed that they or their colleagues were laid-off for COVID-19 related reasons.
  • 64% said they started working remotely.
  • 63% of companies opted for diverting SEO budgets to PPC.
  • 46% of businesses lost essential customers for the last several months, while 12% claimed they enjoyed a surge in new ones.
  •  40% of respondents confirmed their salaries were cut, while 9% of businesses had plans to turn such changes to reality.
  • 28% observed a decrease in traffic compared to 27% that experienced the opposite.
  • Anti-crisis plans were developed and brought to life by 19% of companies.

Survey participants

Precisely 4,511 respondents opted for the survey. The USA, Germany, and Spain are the countries where most participants are based.

The majority of respondents were aged between 22 and 35, and more men participated in the study. For more details about the gender and age distribution of the respondents, please refer to the charts below: 

SEO and PPC specialists, digital marketing specialists, social media, content, and email marketers were among the participants. Their professional experiences ranged from one year to more than 10 years in the field. 

digital marketing survey - participant details digital marketing survey - participant job details digital marketing survey - participant expertise level details digital marketing survey - company type

What are the changes?

SEO budget redistribution

To avoid losses in online sales, 63% of respondents confirm their SEO budgets were redistributed. Thus, contextual advertising gains maximum attention.

This goes to prove that businesses rethink their long and short-term objectives. The shift to short-term goals signifies that companies intend to minimize the influence of quarantine on their key business performance indicators. 

Work from home

Now, as this article gets typed out, many of us stay at home and work remotely. It didn’t take much time for the many to adjust their businesses and tweak the internal processes quickly. This has helped many business owners to keep their businesses running while staying safe.

digital marketing survey - work from home stats

Thus, 64% of respondents confirmed they worked from home, while as few as 6% of Marketing Managers kept working in offices. Additionally, some employers allowed their employees to choose where they wanted to work.

Changes in customer churn

46% of respondents said that they didn’t have the luck to keep several of their customers. These discouraging numbers have led many businesses to focus on improving their products and services, thus doing their best to retain a loyal customer.

Meanwhile, 12% of the survey participants said they had managed to attract new customers during the quarantine.

customer churn stats

Fluctuations in sales

An insignificant drop in sales was recorded by 27% of respondents, while 26% claimed a dramatic decline in sales.

There are also some comforting numbers as the effects of the pandemic are different depending on a business niche. 18% of the survey participants mentioned a sales uplift.

For as many as 13%, there was no change in the number of sales. No news is good news. Well, it might be so during these tough times for many entrepreneurs.

Shifts in online traffic volumes

According to the survey results, online projects enjoy a traffic boost in 27% of cases. 15%  of respondents shared data about a dramatic decline in their online projects, while 28% suffered a slight sales dip.online traffic volume stats

What actions have companies taken to adopt?

Changes are inevitable. Practically 70% of businesses agree with that. Today, customer retention is having the upper hand. We all know that it’s easier to retain a customer than to acquire, and businesses start paying more attention to their loyal customer bases.

As a result, we can see them:

  • Offer discounts (23%)
  • Provide anti-crisis deals (19%)
  • Make specific products or services free (18%)
  • Adapt products/services costs to local currencies (8%)

customer retention efforts of digital marketing companies

Factually, customer-business relationships become more omnichannel and personalized. More than ever before, entrepreneurs need to acknowledge their customers’ needs and make data-driven decisions at every step of interaction with the clients.

Bottom line

Many companies are concerned about the new reality we live in and the new conditions of running a business. Most marketing professionals are convinced that changes in how we do marketing must be made, which also implies an increase in the work volumes. This will allow taking down the harmful effects of the coronavirus pandemic, stabilizing sales, and quickly returning to pre-quarantine business performance indicators.

Eugene Lata is the VP of Marketing and Board Member at Serpstat, an all-in-one SEO platform. His expertise includes marketing, lead generation, SEO, and building smart, innovative marketing teams.

The post Digital marketing during COVID-19 times: Data-driven insights appeared first on Search Engine Watch.

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The data-driven approach to making backlink analysis decisions

May 30, 2020 No Comments

30-second summary:

  • The pandora’s box opened when the link building game got out of control at some point ultimately leading to lower-quality but better-linked pages on top of search results – and that’s when Google started taking counteractions.
  • Whether you or Google like it or not, backlinks remain the crucial part of Google’s algorithm, and consequently, backlink analysis remains the most important step to organic visibility.
  • However, everyone in our industry keeps facing the same question again and again: How to tell good links from the bad ones?
  • All of the SEOs working with sites with more than 20 pages and brands with more than $ 200 budget know that looking at each backlink is hardly possible.
  • Is there a data-driven approach to link building? Ann Smarty helps you create a data-driven backlink analysis strategy.

Backlink analysis has always been one of the toughest tasks of digital marketers and one SEOs have never really found an agreement upon.

And Google has never been really too helpful in ending that debate once and for all.

A quick look into the history of link building

A decade or so ago Google had told us to get other webmasters to link to our pages and even provided us with a tool – PageRank Toolbar – to measure the effectiveness of our link building efforts.

That’s when the Pandora box was opened and no one has been able to close it ever since.

The link building game got out of control at some point ultimately leading to lower-quality but better-linked pages on top of search results – and that’s when Google started taking counteractions.

Penguin updates and manual penalties followed discouraging the site owners from attempting to manipulate Google’s algorithms. “Get backlinks” in Google’s guidelines was revised into “Build high-quality content”, and “link building” acquired a “spammy tactic” connotation.

Yet, no matter how much Google is trying to push away the “link building” agenda, digital businesses are unable to put it aside. In fact, the more Google is fighting bad links, the more emphasis it puts on backlink analysis and acquisition services.

Whether you (or Google) like it or not, backlinks remain the crucial part of Google’s algorithm, and consequently, backlink analysis remains the most important step to organic visibility.

In fact, backlink analysis is helpful on both fronts:

  • Identifying and removing/disavowing low-quality links, those probably sending poor signals to Google, may trip a filter and revive previously earned high rankings.
  • Identifying high-quality link acquisition methods will improve rankings.

While the importance of backlink analysis is clear to everyone who is not living under the rock, everyone in our industry keeps facing the same question again and again: How to tell good links from the bad ones?

When you look at a backlink, you can mostly tell whether it is natural and helpful. But all of the SEOs working with sites with more than 20 pages and brands with more than $ 200 budget know that looking at each backlink is hardly possible.

There’s simply no business implications for “tell it when I see it” concept. So what to do?

Is there a data-driven approach to link building?

I was actually inspired to write this article by stumbling across this article on data-based decision making listing multiple benefits of using data over instincts when making business decisions.

Today, the top companies around the world use data to make decisions about their business. The reason they’re leading the way is that they’ve gained a strategic advantage over their rivals simply by shifting their focus to data rather than relying on business acumen alone. 

The question is, how does this apply to link building?

Simply put, link building and backlink acquisition are crucial for any business presence and visibility in organic search results. This means they fall under the “business decisions” category which means they are basically unthinkable without data to support them.

But while we recognize the importance behind data, which data can we use to make link building and link removal decisions.

Ever since Google’s toolbar PageRank has been deprecated, marketers have no reliable ways to automatically tell a good link from a bad link.

Or do they?

Focusing on a single source of data is dangerous

Lots of marketers are content to judge a link page quality by looking at one particular source, like Moz DA.

And if you have a hard time explaining to anyone why they shouldn’t rely on any particular number, let me make it very easy for you:

None of the current numbers assessing the authority of a web page or a quality of a particular backlink comes from Google.

Do you need a more convincing argument?

It should be clear to any business owner at this point: You cannot achieve success with one of the marketing channels by 100% relying on a third-party source.

Yet, good link building data exists

In fact, when we say don’t trust numbers when it comes to link building or analysis, we mean “no one source”.

Solid link building data exists and not using it means missing valuable growth opportunities.

The smartest link building approach is about learning to combine multiple data sources and learning to identify patterns (to embrace or avoid).

There are multiple backlink research sources including link-only ones (Majesting and Link Assistant) and multi-feature platforms (SEMrush and Ahrefs). There are also newer platforms that are entering the industry that are worth looking at. Serpstat is the most recent example that claims to include one trillion backlinks for 160 million domains:

This is how different two backlink databases can be: 50% on average.

Source: Serpstat

At Internet Marketing Ninjas, for every backlink we acquire, we pull a crazy amount of data, including:

  • Number of domains referencing a linking page (based on all of these: Ahrefs, SEMrush, Majestic, and Moz)
  • Number of links from Wikipedia pointing to that domain
  • Stats on the author assigned to the linking page (number of pages they authored, number of quotations from all over the web, and more)
  • Number of .gov and .edu links pointing to the linking page
  • How many other links that page has

Again, none of those stats is useful on its own but when looking at all of those numbers, you can be pretty confident of the value of that link.

To help you create your own data-driven link building decisions, here are a few helpful tools and resources:

  • Use multiple tools. I know it may be costly but some free or freemium alternatives may help. Many of these plugins, for example, are free and lots of them include the link analysis component.
  • It’s time we rethink how we measure influencers for SEO.

Conclusion

Backlink analysis is the most misunderstood task in our industry. You will see absolute extremes floating around: From experts solely relying on Mox DA to those denying the value of any number whatsoever.

Yet, the task cannot be successfully accomplished without accumulating and assessing data, so the answer is in embracing a holistic approach, that is, using a lot of data sources and making your decisions based on all of them.

Ann Smarty is the blogger and community manager at Internet Marketing Ninjas. She can be found on twitter @seosmarty.

The post The data-driven approach to making backlink analysis decisions appeared first on Search Engine Watch.

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Lessons from leaders: A data-driven approach helps deliver engaging, relevant messages

October 7, 2019 No Comments

As marketers, we know how important it is to understand our customers and reach them at just the right moment. We also know that consumers have more control of their digital environments than ever — and that they expect us to consistently make recommendations in line with their interests, personalities, and behaviors.1 So how can we regularly communicate in a relevant way with all of our customers?

According to our new report on MIT Sloan Management Review, success starts with a strategy that’s backed by data. In the report, The Data-Driven Transformation, we speak with marketing leaders from Bayer, Tapestry Inc. (the parent brand for Coach, kate spade new york, and Stuart Weitzman), and Sprint. They open up with first-hand insights about transforming their teams to be more efficient, accurate, and agile. Here’s a few key insights from the research — and some words of wisdom from these top analytics pros.

Move toward a unified technology stack — and educate as you go

A recent study by the Association of National Advertisers showed that top marketing performers are the same companies that spend the most money on marketing technology.2 In many ways, their investments are paying off, but for those still using separate solutions for separate channels, there’s greater potential. Unifying their tech under a single, shared system could bring fuller, more tailored consumer insights — not to mention an easier way to evaluate what’s working and what’s not.

Jeff Rasp, director of digital strategy for Bayer’s Consumer Health division, did just that, helping reimagine his team’s approach to data. He oversaw the creation of a new marketing insights platform to consolidate data under a single customer ID, and also helped build the company’s first attribution model to evaluate their success.

Assemble teams with the analytics skills to uncover actionable insights

To deliver the right messages at the right times, marketing organizations need data scientists, mobile developers, and other data professionals. For Rob Roy, chief digital officer at Sprint, that meant building a new in-house analytics team to take operations over from external partners.

“We needed to get the right people who know how to build the architecture to house all the data,” Roy explains.

Once he found them, Sprint worked to integrate data across channels — from web and social media to retail and display — allowing the team more advanced customer segmentation capabilities.

Encourage collaboration across teams

A recent McKinsey study showed that 51% of top-performing marketers were part of a networked organization — one where cross-functional teams come together as needed. Parinaz Vahabzadeh, VP of global data labs at Tapestry, is one leader who’s made sure her team collaborates as a single unit.

“Our mandate is to democratize the data,” explains Vahabzadeh. “As a small, centralized team, we need to find ways to focus on the most impactful projects and also enable the broader teams to run analytics independently.”

Find out more

Want the full stories behind how these three brands are reimagining what they can do with data to reach their customers in relevant ways? Download the full report to learn more.

1-2 MIT SMR Custom Studio/Google, “The Data Driven Transformation,” January 2018


Google Analytics Blog


Catalyst raises $15M from Accel to transform data-driven customer success

July 30, 2019 No Comments

Managing your customers has changed a lot in the past decade. Out are the steak dinners and ballgame tickets to get a sense of a contract’s chance at renewal, and in are churn analysis and a whole bunch of data science to learn whether a customer and their users like or love your product. That customer experience revolution has been critical to the success of SaaS products, but it can remain wickedly hard to centralize all the data needed to drive top performance in a customer success organization.

That’s where Catalyst comes in. The company, founded in New York City in 2017 and launched April last year, wants to centralize all of your disparate data sources on your customers into one easy-to-digest tool to learn how to approach each of them individually to optimize for the best experience.

The company’s early success has attracted more top investors. It announced today that it has raised a $ 15 million Series A led by Vas Natarajan of Accel, who previously backed enterprise companies like Frame.io, Segment, InVision, and Blameless. The company had previously raised $ 3 million from NYC enterprise-focused Work-Bench and $ 2.4 million from True Ventures. Both firms participated in this new round.

Catalyst CEO Edward Chiu told me that Accel was attractive because of the firm’s recent high-profile success in the enterprise space, including IPOs like Slack, PagerDuty, and CrowdStrike.

When we last spoke with Catalyst a year and a half ago, the firm had just raised its first seed round and was just the company’s co-founders — brothers Edward and Kevin Chiu — and a smattering of employees. Now, the company has 19 employees and is targeting 40 employees by the end of the year.

Team Photo

In that time, the product has continued to evolve as it has worked with its customers. One major feature of Catalyst’s product is a “health score” that determines whether a customer is likely to grow or churn in the coming months based on ingested data around usage. CEO Chiu said that “we’ve gotten our health score to be very very accurate” and “we have the ability to take automated action based on that health score.” Today, the company offers “prefect sync” with Salesforce, Mixpanel, Zendesk, among other services, and will continue to make investments in new integrations.

One high priority for the company has been increasing the speed of integration when a new customer signs up for Catalyst. Chiu said that new customers can be onboarded in minutes, and they can use the platform’s formula builder to define the exact nuances of their health score for their specific customers. “We mold to your use case,” he said.

One lesson the company has learned is that as success teams increasingly become critical to the lifeblood of companies, other parts of the organization and senior executives are working together to improve their customer’s experiences. Chiu told me that the startup often starts with onboarding a customer success team, only to later find that C-suite and other team leads have also joined and are also interacting together on the platform.

An interesting dynamic for the company is that it does its own customer success on its customer success platform. “We are our own best customer,” Chiu said. “We login every day to see the health of our customers… our product managers login to Catalyst every day to read product feedback.”

Since the last time we checked in, the company has added a slew of senior execs, including Cliff Kim as head of product, Danny Han as head of engineering, and Jessica Marucci as head of people, with whom the two Chius had worked together at cloud infrastructure startup DigitalOcean.

Moving forward, Chiu expects to invest further in data analysis and engineering. “One of the most unique things about us is that we are collecting so much unique data: usage patterns, [customer] spend fluctuations, [customer] health scores,” Chiu said. “It would be a hugely missed opportunity not to analyze that data and work on churn.”


Enterprise – TechCrunch


Catalyst raises $15M from Accel to transform data-driven customer success

July 30, 2019 No Comments

Managing your customers has changed a lot in the past decade. Out are the steak dinners and ballgame tickets to get a sense of a contract’s chance at renewal, and in are churn analysis and a whole bunch of data science to learn whether a customer and their users like or love your product. That customer experience revolution has been critical to the success of SaaS products, but it can remain wickedly hard to centralize all the data needed to drive top performance in a customer success organization.

That’s where Catalyst comes in. The company, founded in New York City in 2017 and launched April last year, wants to centralize all of your disparate data sources on your customers into one easy-to-digest tool to learn how to approach each of them individually to optimize for the best experience.

The company’s early success has attracted more top investors. It announced today that it has raised a $ 15 million Series A led by Vas Natarajan of Accel, who previously backed enterprise companies like Frame.io, Segment, InVision, and Blameless. The company had previously raised $ 3 million from NYC enterprise-focused Work-Bench and $ 2.4 million from True Ventures. Both firms participated in this new round.

Catalyst CEO Edward Chiu told me that Accel was attractive because of the firm’s recent high-profile success in the enterprise space, including IPOs like Slack, PagerDuty, and CrowdStrike.

When we last spoke with Catalyst a year and a half ago, the firm had just raised its first seed round and was just the company’s co-founders — brothers Edward and Kevin Chiu — and a smattering of employees. Now, the company has 19 employees and is targeting 40 employees by the end of the year.

Team Photo

In that time, the product has continued to evolve as it has worked with its customers. One major feature of Catalyst’s product is a “health score” that determines whether a customer is likely to grow or churn in the coming months based on ingested data around usage. CEO Chiu said that “we’ve gotten our health score to be very very accurate” and “we have the ability to take automated action based on that health score.” Today, the company offers “prefect sync” with Salesforce, Mixpanel, Zendesk, among other services, and will continue to make investments in new integrations.

One high priority for the company has been increasing the speed of integration when a new customer signs up for Catalyst. Chiu said that new customers can be onboarded in minutes, and they can use the platform’s formula builder to define the exact nuances of their health score for their specific customers. “We mold to your use case,” he said.

One lesson the company has learned is that as success teams increasingly become critical to the lifeblood of companies, other parts of the organization and senior executives are working together to improve their customer’s experiences. Chiu told me that the startup often starts with onboarding a customer success team, only to later find that C-suite and other team leads have also joined and are also interacting together on the platform.

An interesting dynamic for the company is that it does its own customer success on its customer success platform. “We are our own best customer,” Chiu said. “We login every day to see the health of our customers… our product managers login to Catalyst every day to read product feedback.”

Since the last time we checked in, the company has added a slew of senior execs, including Cliff Kim as head of product, Danny Han as head of engineering, and Jessica Marucci as head of people, with whom the two Chius had worked together at cloud infrastructure startup DigitalOcean.

Moving forward, Chiu expects to invest further in data analysis and engineering. “One of the most unique things about us is that we are collecting so much unique data: usage patterns, [customer] spend fluctuations, [customer] health scores,” Chiu said. “It would be a hugely missed opportunity not to analyze that data and work on churn.”


Enterprise – TechCrunch


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