New galleries for Data Studio Community Visualizations
Showcase gallery for Community Visualization reports
The Data Studio team recently launched the Community Visualization Report Gallery.
There, you can explore how others in the community have leveraged Community Visualizations to make the most of their data and dashboards.
Public Partner Visualization Gallery
Additionally, we’ve added a new gallery of Partner Community Visualizations that we’ve made available. Browse them in the new Data Studio Visualizations gallery.
Click-to-add Partner Visualizations
To add these Partner Visualizations to a report, click “Explore more” in the Community Visualizations drop down. There, you can browse and install a variety of partner-built charts, including funnel visualizations and Gantt charts.
Community Visualizations can add to a Data Studio dashboard in different ways – from providing custom charts and styling to integrating calculations with reporting.
Statistical analysis with Community Visualizations
Anvil Analytics + Insights works to bring data-driven decision making to all of their work, including optimized paid media campaigns. They used Community Visualizations to build their own Chi-Square statistical analyzer.
Several Anvil customers noticed that channels in Google Ads and Analytics converted at different rates, and wanted to know if the variance in conversion rates was statistically significant.
Prior to using Community Visualizations, the Anvil Insights team manually exported the data out of Google Analytics into a separate tool, then ran the statistical analysis. Depending on where Anvil ran the analysis, the results were either stored separately from their reports, or not stored at all. Every time they wanted to test a different hypothesis or run a different variation of the test, they had to repeat the same time-intensive process.
In order to speed up hypothesis testing and integrate the tests and results into Data Studio reports, Anvil used Data Studio Community Visualizations and built a Chi-Square calculator within a week.
Anvil’s calculator takes in data, just like any Data Studio chart. Once the calculation is complete, the analyzer presents the statistical significance, and either calls the viewer’s attention to a relationship in the data, or comments that there was nothing of note in the data. Now, all it takes to test new hypotheses is switching out the data for the component, just like you would for any other Data Studio chart. See it live.
“This has been a much faster way to find statistical significance in our campaigns and in other hypotheses we want to test. Anvil’s Director of Analytics and Decision Science, Brett Lohmeyer says, “The best part is that it gives us an easy way for our team to better communicate the value of using statistical significance to our clients.”
Try it yourself
Check out the new in-product Partner Visualizations Gallery to browse and add new partner-built Community Visualizations to your reports. To build your own Community Visualizations, check out the developer documentation.
As people use Data Studio throughout their organizations, IT administrators have asked to manage how Data Studio can be used. Today, we’re launching three free enterprise features providing IT administrators new visibility and control over Data Studio in their organization.
Organization management through Cloud Identity integration
Data Studio now integrates with Google Cloud Identity to provide organization-wide administrative capabilities. With this integration, Cloud Identity admins can manage who can use Data Studio and how they can use it. Existing G Suite and Cloud Identity customers get Data Studio integration out of the box, and can start using the new Data Studio administration features today. Customers using other identity providers, such as Active Directory, can synchronize their users with Google Cloud Identity, so that creating, suspending, and deleting users happens in one place.
Enterprise audit logging
Data Studio now offers audit logging, providing IT admins organization-wide visibility into Data Studio usage, similar to that available for apps like Drive and Calendar. For example, admins can understand which users are creating Data Studio reports, and who they are sharing those reports with. Admins can also identify which reports have the most engagement, to scale successful reports across the organization. With custom alerts, you can monitor potentially risky activity like external sharing of data sources, and can export audit logs to BigQuery and use Data Studio to drill into the details. Learn more.
Organization sharing policies
New Data Studio sharing policies allow you to reduce the risk of data exfiltration. You can set limits to prevent users from sharing reports outside of your organization, or make sure they don’t expose company data by disabling public link sharing.
Sharing policies offer you the flexibility to define sharing permissions that meet your business needs. You can give certain users the ability to share reports externally, while allowing other users to share only within the organization. Learn more.
There’s no charge for audit logging or sharing controls — they’re included with every edition of G Suite and Cloud Identity, including Cloud Identity Free. We’re committed to making Data Studio a solution that works for businesses of all sizes, and we’ll continue to build on this foundation. That way, everyone in your organization can uncover insights that matter, and you can rest assured knowing that your valuable business data is safe.
- Third-party data is being phased out by big tech, making first-party data indispensable
- First-party data is willingly provided by users, helping you build a consumer profile
- Internet users are cautious about providing their data but will do if rewarded
- Tracking pixels, CRM platforms, surveys, and encouraging interaction and registrations are all effective ways to capture first-party data
- First-party data must be used responsibly, repaying the trust placed in a business by consumers
When doing business online, data is arguably the greatest currency of all. By obtaining reliable data about your target audience, an effective and bespoke marketing plan can be devised. This will convince customers that you understand their unique needs, desires, and pain points.
Alas, not all data is created equal. As the influence of the internet grows, and the fallout of the Cambridge Analytica scandal continues to reverberate, consumer privacy is more important than ever. Any online business needs to build a consumer profile in an ethical, reliable manner. This makes the collection of first-party data critical.
What is first-party data?
First-party data is consumer information collated directly by your business, based on user behavior. This data can be used to build a profile of your target audience, tailoring your marketing and user experience accordingly.
What is the difference between first-party, second-party, and third-party data?
As discussed, first-party data is user information collated directly from your website. We will discuss how you can obtain first-party data shortly. Let’s clarify the difference between this approach and second- or third-party data, though.
Second-party data is essentially the first-party data collated by another business. This may be shared between two websites for an agreed common good. However, second-party data remains private. It will not be made available to the public and cannot be purchased.
Third-party data is that which you purchase, usually from a data management platform (DMP) or consumer data platform (CDP). These platforms harvest data from users based on their online habits. These are known as tracking cookies. It is important to note that third-party data is not gained through any personal relationship with consumers.
The use of third-party data is slowly being phased out. Internet users are growingly increasingly security-conscious and are looking to shape online privacy policies. Google has announced that they will be removing third-party cookies from 2022, while the Firefox and Safari browsers have all already done so. With Google Chrome accounting for some 65 percent of global web browser traffic, the impact of this will be keenly felt.
In essence, third-party data is a dying art, and second-party data ultimately belongs to somebody else. This means that first-party data collation should be a priority for any online business, now and in the future.
How does first-party data help a business?
As intimated previously, first-party data is used to build a consumer profile. Think of this as market research straight from the horse’s mouth. By monitoring how users interact with your web presence, you can offer them more of what they want – and less of what will not interest, or even alienate, them. After all, there is little to gain by marketing a steakhouse restaurant to somebody that exclusively shows interest in a vegan lifestyle.
Perhaps the most effective example of marketing through first-party data is Amazon. We’ve likely all purchased something from Jeff Bezos’ empire at one time or other. Even if a conversion was not completed, you may have browsed the products on offer. Amazon uses this data to build personalized recommendations on your next visit.
It’s not just a tool for direct interaction on a website, though. First-party data is also invaluable for advertising. By learning about the habits of a user, tailored marketing can reach them on social media. This is a powerful form of inbound marketing that piques consumer interest.
Consumers that have previously been exclusively interested in red circles may be tempted to experiment with a blue triangle, but they are likelier to stick to type. By embracing first-party data, you can meet customer needs before they ask. This is a cornerstone of success, especially in the competitive world of online commerce. After all, 63 percent of customers now expect at least some measure of personalization from any service provider.
Creative ways to capture first-party data
Capturing first-party data is a delicate art. With consumers wary about how much the tech industry knows about them, this data may not be provided freely. You’ll need to offer something in return. 90 percent of consumers will willingly offer first-party data if you make it worth their while.
Most importantly, you’ll need to be transparent about how first-party data is captured and used. Consumers are wary by default, and you’ll need to earn their trust. An open acknowledgment of the data you collect, and how it will be used, is the first step to achieving this faith.
Seven great opportunities to capture first-party data
Let’s discuss some ways to help your business obtain first-party data that will help elevate your business to the next level.
1. Add tracking pixels to a website
Tracking pixels are tiny – usually no bigger than 1 x 1 – pixels that users rarely notice. These are installed in websites through coding and collate first-party data about user habits.
This could include what pages are viewed, the adverts that garner interest, and personal information such as whether the user browses through a mobile or desktop appliance.
This all sounds like cookies, but there is a crucial difference. Cookies can be disabled or cleared, as they are saved within the browser of the server. A tracking pixel is native to your website, so it will capture data from every visit, regardless of what settings the user enables.
2. Use a CRM platform
Customer relationship management (CRM) software is growing increasingly popular with online businesses. Chatbots are perhaps the best example of this. Chatbots are not for everybody – many consumers still prefer to interact with a human – but 90 percent of businesses claim that chatbots have enhanced the speed and efficiency of problem resolution.
What’s more, chatbots effortlessly capture first-party data. If a user has an issue or concern, they may grow weary of waiting on hold on the phone for 15 minutes and hang up. That lead is now potentially lost forever, and you’ll never know what they were looking for. Even if a chatbot cannot encourage a user to convert, you’ll have an idea of what they were interested in. This will aid in targeted marketing and user personalization in the future.
3. Reward users for sharing their data with you
As mentioned previously, customers want to be rewarded for their exchange of data. Ideally, this will be an immediate, tangible reward such as a discount. At the very least, provide evidence that you are personalizing your service to unique consumer needs.
Not every business will be able to offer immediate fiscal motivation to every user. There are other ways to reward consumers, though. Monthly giveaways are a good example, especially when advertised and managed through social media. Encourage people to like and share a post, promising to provide an incentive to one lucky winner at the end of the month.
This is easily dismissed as a cynical marketing ploy, so you’ll need to follow through on your promise. More importantly, you’ll need to make it clear that you have done so. If consumers believe that they are in with a shot of something for nothing, though, they are likelier to consider the use of their data a fair exchange.
4. Encourage interaction
Buzzfeed may not the first place many look for hard-hitting journalism, but it enjoyed stellar traffic for many years. Why? Because it encouraged interaction through goofy online quizzes that offered easy ways to harvest consumer data.
This isn’t necessarily a model for every website to follow. You need to protect your brand reputation. Inviting people to learn which pizza topping defines them best may do more harm than good. Similar exercises surrounding your business may encourage interaction though. A quiz about your business sector, promising a reward for completion, will attract interest.
Any competent SEO services agency will tell you that quizzes and other interactive elements on a page can also have the bonus of helping with SEO. This is because an important metric for Google when evaluating the quality of your website is “time spent on page”. If Google can see that your visitors are spending several minutes looking at a page, then this is a positive signal that the page is engaging and interesting to visitors.
Another strategy could be unlockable social media posts. Consumers will be intrigued about what you are offering behind a shield. Paywalls are likely to deter, but promising content-centric rewards if people share their data can be effective – if the result is worth the sacrifice.
5. Conduct surveys
The march of technology ensures that all consumers now have a voice. They expect this to be heard. Never lose sight of the fact that consumers hold the power in the 21st Century. Negative reviews of products and services can cost a business up to 80 percent of potential conversions.
The simplest way to achieve this is by issuing surveys to your existing customers, and even potential leads. Do not expect a 100% return rate, especially if you do not offer a reward for the time of consumers. Some will leap at the chance to express their opinions though, providing you with valuable first-party insights.
6. Encourage registration
If you run an ecommerce website, conversions are the most important bottom line of all. This means that many businesses will, understandably, offer services that increase the likelihood of making a sale. This could include guest checkout, a policy preferred by half of all online consumers.
The issue with guest checkout is that it captures less data than signing a customer up. Many consumers choose guest checkout as it’s faster, provides more privacy (especially when paying with an e-wallet rather than a credit card), and – theoretically – protects their inbox from unwanted marketing communication.
As we have established though, many consumers will provide data if you offer something in return. The most popular example of this is a discount on the first purchase. Couple this with a promise of personalized offers and an enhanced shopping experience and you’re likelier to see more sign-ups.
Just be careful about what data you are asking for. Be sure to explain why information is important. Unless a credit check is necessary, for example, many customers may be reluctant to share their date of birth. If you promise to offer exclusive offers around their birthday, however, your argument will be much more persuasive.
7. Host events
Younger consumers value experience over results. The days of gaining unstinting loyalty through providing goods or services at an affordable price are over. The rise of social media, and its omnipresence in the lives of Millennials and Generation Z, means that a personal connection is required.
Live events can provide this. Host an AMA, whereby a senior figure of your business answers questions about your practices. This can also be a great way to reassure consumers that you operate in a sustainable, socially conscious manner – something hugely important to many modern consumers. A live product launch can be another way to attract users.
How does this benefit first-party data? Attending the event will require registration. Even if the number of sign-ups is not mirrored by the eventual attendees, you have gained valuable data. You will also capture insights from those that do attend the event, especially if you encourage interaction.
Mistakes to avoid when capturing first-party data
As we have been at pains to point out, consumer data is a sensitive subject. First-party data is invaluable, but it must be obtained without betraying the trust of consumers. Here are some key pitfalls to avoid in your data collection strategy.
- Do not ask for something for nothing. Data sharing needs to be a quid pro quo exchange
- Avoid getting too personal – only seek data that is relevant to your business model
- Be clear about how the data will be used, offering consumers the opportunity to opt-out if this is their preference
- Shout from the rooftops about your privacy policies. Users can never be made to feel too safe
- Use the data responsibly, offering value to consumers and not abusing the information you have gained. Trust is hard to gain and easy to lose. As Google discovered, unethical use of data that breaches trust can also be very costly
Is your website making the best use of first-party data? Do you have any additional creative suggestions of how this information can be ethically sourced? These are the questions that will define the success of your business going forward. Be sure to hop onto the first-party data train now. It has already left the station and is rapidly picking up speed.
The post Seven first-party data capturing opportunities your business is missing out on appeared first on Search Engine Watch.
Extracting Entity Information From Web Pages with Data Wrappers One of the areas of SEO that is worth exploring involves Semantic SEO, which I wrote about in more detail in the post What is Semantic SEO?. And one of the important patents I wrote about in that post involved Entity Extraction for knowledge graphs and … Read more
By 2025, 463 exabytes of data will be created each day, according to some estimates. (For perspective, one exabyte of storage could hold 50,000 years of DVD-quality video.) It’s now easier than ever to translate physical and digital actions into data, and businesses of all types have raced to amass as much data as possible in order to gain a competitive edge.
However, in our collective infatuation with data (and obtaining more of it), what’s often overlooked is the role that storytelling plays in extracting real value from data.
The reality is that data by itself is insufficient to really influence human behavior. Whether the goal is to improve a business’ bottom line or convince people to stay home amid a pandemic, it’s the narrative that compels action, rather than the numbers alone. As more data is collected and analyzed, communication and storytelling will become even more integral in the data science discipline because of their role in separating the signal from the noise.
Data alone doesn’t spur innovation — rather, it’s data-driven storytelling that helps uncover hidden trends, powers personalization, and streamlines processes.
Yet this can be an area where data scientists struggle. In Anaconda’s 2020 State of Data Science survey of more than 2,300 data scientists, nearly a quarter of respondents said that their data science or machine learning (ML) teams lacked communication skills. This may be one reason why roughly 40% of respondents said they were able to effectively demonstrate business impact “only sometimes” or “almost never.”
The best data practitioners must be as skilled in storytelling as they are in coding and deploying models — and yes, this extends beyond creating visualizations to accompany reports. Here are some recommendations for how data scientists can situate their results within larger contextual narratives.
Make the abstract more tangible
Ever-growing datasets help machine learning models better understand the scope of a problem space, but more data does not necessarily help with human comprehension. Even for the most left-brain of thinkers, it’s not in our nature to understand large abstract numbers or things like marginal improvements in accuracy. This is why it’s important to include points of reference in your storytelling that make data tangible.
For example, throughout the pandemic, we’ve been bombarded with countless statistics around case counts, death rates, positivity rates, and more. While all of this data is important, tools like interactive maps and conversations around reproduction numbers are more effective than massive data dumps in terms of providing context, conveying risk, and, consequently, helping change behaviors as needed. In working with numbers, data practitioners have a responsibility to provide the necessary structure so that the data can be understood by the intended audience.
Rising consumer expectations and changing industry regulations have set higher standards for user privacy and data protection. This has led many businesses to revisit how they are managing data in their Google Analytics accounts. To help, Analytics provides businesses with a variety of features to control how their data is used. Here is an updated overview of controls in Analytics that govern how data is collected, stored, and used–all of which can be adjusted at any time.
Three ways businesses can manage data in Google Analytics:
Control the data settings in your account
You can access various settings in your Analytics account to control how you collect, retain, and share data.
Decide if you need to accept the Data Processing Terms.
The optional Data Processing Terms are meant for businesses affected by the European Economic Area General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and other similar regulations. You can review and accept the terms if needed in your Analytics account, under Account Settings.
Anonymize IP addresses for your Web property.
When you enable IP anonymization in your Web property, Analytics will anonymize the addresses as soon as technically feasible. This may be useful for you to comply with your company’s privacy policies or government regulations. For Apps properties and App + Web properties, IP anonymization is enabled by default.
Disable some or all data collection.
Set the data retention period.
You can select how long user-level and event-level data is stored by Analytics, and whether new events can reset that time period. Once that amount of time has passed, the data will be scheduled for automatic deletion from your account and Google’s servers.
Select what data you share with your support team and Google.
The data sharing settings allow you to customize whether to share Analytics data with Google, including whether to allow Google technical support representatives and Google marketing specialists to access your account when you want support using the product or performance recommendations.
Review your Google signals setting.
The Google signals setting allows you to enable additional features in Analytics like remarketing, demographics and interests reports, and Cross Device reports. You can also further customize this setting to keep Google signals enabled for reporting while limiting or disabling advertising personalization.
Choose whether your data is used for ads personalization
Digital advertising helps you reach people online and drive conversions on your app and website. When you enable ads personalization in Analytics, for example by activating Google signals, you gain the ability to use your Analytics audiences to personalize your digital ads which can improve the performance of your campaigns. You can customize how your Analytics data is used for ads personalization.
Control ads personalization for your entire Analytics property.
You can choose to disable ads personalization for an entire property, which will cause all incoming events for that property to be marked as not for use in ads personalization. You can manage this in the property settings of your account.
Control ads personalization by geography.
If you need to set the ads personalization setting for your property at the geographic level, you now have the ability to enable or disable this setting by country. And in the United States, you can adjust the setting at the state level.
Control ads personalization by event type or user property.
In App + Web properties, you can adjust the ads personalization setting for a specific event type or user property. For example you can exclude specific events or user properties from being used to personalize ads and only use that data for measurement purposes.
Control ads personalization for an individual event or session.
You can also manage whether an individual event or session is used for ads personalization. For example, if you need to obtain consent before enabling the setting you can dynamically disable ads personalization at the beginning of the session and on each subsequent event until consent is obtained.
Independent of these ads personalization controls that Analytics offers to advertisers, users can control their own ads personalization setting for their Google account. Once they’ve turned off this setting, Google will no longer use information about them for ads personalization.
Remove data from Analytics
You can remove your data from Analytics for any reason and at any time. You can request the data to be deleted from the Analytics servers or delete information for a single user.
Request data to be deleted.
If you need to delete data from the Analytics servers, you can submit a request for its removal. There is a seven-day grace period starting from the time you make the request before Analytics will begin the deletion process. All administrators and users with edit permission for your account will be informed of your request and have the ability to cancel the request during the grace period. Similar functionality will be available in App + Web properties soon.
Delete data for individual users.
You are able to delete a single user’s data from your Analytics account. If you have edit permission for the account, you can do this through the User Explorer report in Web properties or the User Explorer technique in the Analysis module in App + Web properties. Data associated with this user will be removed from the report within 72 hours and then deleted from the Analytics servers in the next deletion process. Your reports based on previously aggregated data, for example user counts in the Audience Overview report, won’t be affected. If you need to delete data for multiple users, you can use the Analytics User Deletion API.
Delete a property.
All of the above features are available to use right now. For more information, please visit the Help Center.
We hope that you found this overview of current controls helpful. Google Analytics is continuously investing in capabilities to ensure businesses can access durable, privacy-centric, and easy to use analytics that work with and without cookies or identifiers. Please stay tuned for more in the coming months.
- Analyzing and understanding website data helps enhance potential sales and conversions
- Google Analytics records the exit rate of specific website pages, helping you pinpoint exactly where users abandon your sales filter
- Google Tag Manager can help identify if users are leaving forms uncompleted, leaving you tantalizingly close to conversion without sticking the landing
- Recording and analyzing common user search terms on a website will reveal if consumers are seeking services they are willing to pay for but you do not provide
- Search analysis tools will shine a light on any underutilized and under-monetized website pages, helping you make the most of your PPC budget
In the age of online marketing and data intelligence, every click matters. Traffic is a great metric for the potential success of your business, after all. Alas, traffic means little without conversions. A brick-and-mortar store that sees plenty of footfall but fails to make sufficient sales will be considered a failed business model. The online world is no different. Without conversions, a website is just an expensive – and ultimately unsuccessful – advertising campaign.
A conversion is the completion of any pre-determined action on a website. This could be downloading free content in exchange for joining a mailing list or interacting with the site through social media or a contact form. The gold standard of conversions will always be sales, though. If your product or service is not turning a profit, something needs to change.
By studying and understanding website data, you can pinpoint missed opportunities for sales on your site. Utilizing tools and software, you’ll understand what visitors are looking for and why they bounce without converting.
Data to review
Here are four core KPIs that should be studied to understand why visitors leave your site without making a conversion. By mastering and understanding this data, you can make any necessary adjustments to your website and marketing strategy – potentially reaping financial rewards.
1. Google Analytics exit pages
The exit page of a website, which is tracked on Google Analytics, is the last interaction a user has with your website before terminating a session. Google Analytics records exit pages as a percentage, referring to this as an exit rate.
In an ideal world, the most popular exit page on any website will be the thank you page after completing a conversion. At this stage, the user has concluded their business to the satisfaction of all parties.
If you notice a high exit rate on a different page, it merits investigation. Something about this page is deterring visitors from converting. Ergo, this exit page is potentially responsible for missed sales.
Be aware that an exit rate is not the same as a bounce rate. Bounce rate relates to users that leave a site without any interaction. Exit pages are recorded when users begin the journey toward conversion but fail to complete the process.
By understanding which pages on your website have the highest exit rate, you can improve your sales. Take a look at this page and consider why users are not completing a conversion. Potential explanations include:
- An unclear or weak call to action
- A lengthy sales funnel with too many steps
- Insufficient information about your product or service, failing to convince the user to convert – or too much data, confusing a user and causing them to lose interest
- Lack of preferred payment options (that is, ewallets – not everybody likes to use their credit card online)
Tweak this exit page to improve user experience and convince users to conclude a conversion. This is easier if one page of your website, in particular, has a high exit rate. If exit pages are equally spread throughout your site, it may be worth considering a complete overhaul and refresh of the content.
2. Google Tag Manager
The internet has brought a lot of good to the world, but enhancing patience is not among these benefits. With so much competition out there, users are unlikely to tolerate any kind of interface issues when attempting to complete a conversion. You can use Google Tag Manager to identify these issues.
Form completion is arguably the best use of GTM. If you study the analytics of a form and find that it is frequently being abandoned before completion, something is amiss. You had the user on the end of your hook – they would not have started to fill in the form otherwise. Unfortunately, something made them change their mind and you missed out on a sale.
Use the GTM debugging mode to ensure that a technical hitch was not to blame. If this is the case, it’s time to look inward. Some of the common reasons for users to abandon forms before completion include:
- The form is just too long and cumbersome! Slow and steady may win a race, but it bores the life out of online consumers
- Unnecessary questions. If you’re not selling age-restricted products or services, don’t ask for a user’s date of birth. Unless it’s relevant to the product, do not ask for clarification of gender or race
- Pop-up advertising. Unfortunately, you may be standing trial for the sins of other sites here – previous experiences elsewhere may tarnish a user’s view of all online forms
- Lack of assurance about the safety and security of any data that will be provided. Make it clear that you are not in the business is selling personal information to other businesses
- Lack of mobile device compatibility. Over half of all web traffic now comes from smartphones and tablets. Ensure your form is not fiddly and persnickety to complete on such a device
Source: Google Tag Manager
Using GTM to gain insights into why forms remain uncompleted can be an easy fix, and potentially turn half-completed questionnaires into successful conversions. Don’t miss out on a possible sale for something as prosaic as a needlessly complicated sign-up process.
3. Search records
As we touched upon previously, consumers want to feel understood by a business. The modern visitor to a website will ideally not wish to search to find what they’re looking for. Visitors want to find everything they need before their eyes and to see that your product or service will resolve a particular pain point.
If users are making use of the search function, configure the site to record search terms. This provides the perfect opportunity to study what your potential customers are seeking – and presumably not finding – on your site. If they located what they were looking for, they would likely have completed a conversion.
Understanding what users are searching for means that you can improve and enhance your offering to apply these missing services. Alternatively, it may just reveal that your copy needs a little updating. Check whether users are using terminology that does not match up with keywords used on your site. This is an easy fix with a content refresh and reduces the frustration of being so near but yet so far from a conversion.
This will also have a welcome side-effect of potentially bolstering your SERP standing. Google is moving toward a model of enhanced search equity, which makes your use of copy all the more important. It will be very welcome for a website’s page ranking – and conversion potential – to stand or fall on quality and relevance of content, as opposed to restrictive technical obstacles.
4. Traffic value
To paraphrase George Orwell, “all website traffic is equal, but some traffic is more equal than others.” Some pages on your website will inevitably demonstrate greater potential for sales and conversions. Investing in a search analysis tool can aid you in identifying these pages so you can focus your financial outlay on them. Google Trends can also be an invaluable ally here.
Your website will likely utilize at least one cost-per-conversion model, such as Google Ads. You may be using several, with Facebook Ads (which includes Instagram Ads) and even Microsoft Advertising providing plentiful leads to conversions. While PPC business models are constantly evolving, some tactics are evergreen.
Perhaps the most critical of these is identifying which pages on your site have potential that is not being maximized. By undertaking SEO analysis, you will gain a greater understanding of what users are looking for online. In learning this, you may realize that you are placing too much of a marketing budget on one page when judicious use of keywords on another may yield greater results.
For example, it’s always tempting to place all of your financial muscle on a completion page. We have discussed already how users are looking for a brief and practical conversion funnel. Do not overlook the potential to educate and entertain before pushing for conversion, though. If you embrace – and more importantly, perfect – content marketing, you will convince users to click through to a conversion page after learning more about your offering. This enhances your traffic stats, potentially building brand loyalty in the process.
Now that you are aware of these metrics, use them to calculate your conversions. That’s easily done – just divide the number of conversions by the number of visitors, then multiply the total by 100. How does that number look to you?
If you feel that your conversion rate is lacking in any of these metrics, there are steps that you can take to improve it. These include:
- Simplifying any forms and streamlining your sales filter
- Improve and simplify the copy on pages with a high exit rate
- Considering adding a pop-up with a renewed CTA – or even the promise of a discount or freebie – when a user tries to close a common exit page
- Review your search records and ensure your offering matches consumer needs and expectations
- Keep up to date with search trends and ensure you are monetizing the right pages on your website
Follow these steps and you’ll potentially see your conversions soar. Few things are more frustrating than missing out on a sale that came enticingly close. These minor improvements will not take much work but could make a real difference to your bottom line.
What is a website conversion?
Any website will contain a range of actions for visitors to complete. This could be signing up for a newsletter mailing list, sharing a post on personal social media channels, making a query through a contact form, or ideally making a purchase. If a visitor to your website completes this action, it is considered a conversion. The number of people that do so compared to your traffic quantity is referred to as a conversion rate.
What is a good conversion rate for a website?
This depends on a range of factors, including your industry and your anticipated return on investment. A website that operates on a cost-per-conversion model, such as Google Ads, needs a higher conversion rate to turn a substantial profit. The average conversion rate on this platform is circa three percent. What matters most is that you are seeing a return on your investment – and that your conversion rate continues to grow, not shrink.
How to increase the conversion rate on a website?
The most effective way to increase a conversion rate is to make the process as fast and simple as possible for consumers. Create a superior user experience by making it obvious what a visitor needs to do to convert, and by removing any unnecessary steps from the resulting filter. Every additional action you ask of a user gives them another opportunity to lose patience and walk away.
How to calculate a website conversion rate?
There is a simple formula for calculating the conversion rate of your website. Track your conversions over a set period, divide this by the number of visits to the website in this time, then multiple the total by 100. For example, a website that enjoys 700 conversions from 12,500 visitors over 30 days has a monthly conversion rate of 5.6%.
How to set up conversion rate tracking on your website?
Any website must track conversions to ensure optimum efficiency and return on investment. Major platforms like Facebook Ads and Google Ads have in-built tracking facilities. Learn how to utilize these tools and turn the data to your advantage.
Joe Dawson is Director of strategic growth agency Creative.onl, based in the UK.
The post Four ways to use your website data to discover missed sales opportunities appeared first on Search Engine Watch.
- Data storytelling is the process of combining graphics and narratives to help audiences understand complex data
- There are eight types of graphs and charts that marketers can use to tell data stories
- This guide will help you understand why data storytelling is important and what best practices you should follow
We’re seeing the growing importance of storytelling with data in 2021—primarily because of the amount of data being shared with audiences over the past year.
But data needs to make sense to people if it’s to lead to better engagement and increased conversions. That’s where visualization comes in.
According to Venngage’s recent study, data storytelling has become a popular tool in an organization’s arsenal, with 48 percent of marketers creating data visualizations weekly.
In this article, we will share why businesses are turning to data storytelling to tell their brand stories and to capture the imagination of their customers.
Why is storytelling with data important?
Data-driven storytelling combines data and graphics to tell a compelling story. It also gives the data more context so audiences can understand it better.
The visual representation of data lies can show readers patterns and connections they may not have deduced on their own.
That’s what makes them such a necessary tool in a small business’ arsenal—data graphics can help businesses track their performance and set goals.
Kinds of data visualizations for storytelling
There are numerous visual tools available to render data—they highlight why data visualization is important.
Some of the kinds of data visualizations for storytelling include:
- Bar Graphs
- Bubble Charts
- Line Charts
- Pie Charts
- Scatter Plots
Each visualization technique serves a purpose. Bar graphs and charts are ideal for creating comparisons, whereas line charts show linear relationships.
Maps show geographical data, like this example about the languages of the world.
Pie charts share data according to set categories, while scatter plots show relationships between multiple variables.
To understand which charts and graphs to use to tell your data story, you can refer to the below infographic.
Five advantages of data storytelling
What advantages can businesses expect when storytelling through data?
These are the questions that marketers and designers ask themselves before undertaking such a design-heavy project.
But there are several uses for data graphics that make them worth investing time and effort into.
1. Provides deeper analysis into information
If you look at the types of visualizations described above, you can see how they provide greater insight into information.
A text post or report can do the same work but will require much more labor from the reader—increasing the chances of them leaving your page for shorter content.
A graphic, on the other hand, tells the reader the same information in a much shorter time. This improves engagement rates and conversions.
Visuals can also convey patterns easily allowing the reader to analyze information quickly by connecting the dots themselves.
2. Promotes problem-solving
Data stories are succinct materials that boost the problem-solving process and improve productivity.
This is because decision-makers don’t have to read reams of text or sift through information on their own—the graphics do the work for them and speed up problem-solving.
3. Engages internal and external audiences
Content marketing is geared toward engagement—and that’s why strong visuals that catch the eye are so important.
Visuals are more attractive than blocks of text—and data graphics that are well-made even more so than others.
This is because a data story is compelling in itself—numbers, percentages, relationships, and connections are all reasons for a reader to stop what they’re doing and look at your graphic.
As a result, you increase traffic and views to your content and your website, all while promoting a favorable impression of your brand.
4. Improves reporting abilities
Reports are part and parcel of business life. A great data story is key to a memorable and powerful analysis, like this simple but elegant finance infographic template.
There is so much data involved in creating reports—if they are articulated through numbers and tables, your audience will be lost, and worse, bored.
That is why great data storytelling is so important in report-making, not just to keep people interested but to tell a good story.
5. Wide reach
Graphics can be repurposed in multiple ways and for a variety of channels. Social media platforms like Twitter, which are chockful of information, require a strong visual to get attention.
That attention can be generated through data storytelling. Bite-sized visuals arrest the viewer as they’re scrolling through their feed—they’re also easy to absorb and more shareable.
Visualized data makes for great content whether for social channels, newsletters, blog posts, or website landing pages.
A great graphic has the potential to go viral, widening the reach of your content and influence.
Data storytelling best practices
Paying heed to the importance of visualizing data means following a few best practices. You can’t create visuals without having a goal.
You also need to understand the subject matter and the needs of your audience so your data tells the story you want it to and engages your readers.
Here are the six best practices for creating visualizations that will boost customer retention.
Create visual hierarchies
Hierarchies are necessary for people to read and interpret your data. Visual hierarchies are a key component of data storytelling because they help readers create context and patterns.
Since you don’t want to write too much text to explain your graphic, hierarchies are the best way to convey context. Here are the best ways to build visual hierarchies and context:
- Placement of elements from top to bottom
- Grouped elements
- Varying colors
- Varied visual styles
- Increasing font sizes
Users will be able to deduce the relationship between data and elements using the above methods.
Build trust into data visuals
The benefits of visualization are completely lost if you can’t elicit trust in the people viewing your information.
When we put statistics together for studies at Venngage, we survey hundreds, if not thousands, of respondents before beginning the design process.
This is necessary to avoid cherry-picking data, which can be misleading, as this graph shows, and accidentally designing bad infographics.
It is always best to compile data from trusted sources that are unbiased. Verify that data with at least two other sources so you know that the data is representative of the information.
Only then should you move into the design phase. When creating your visuals, avoid distortion as much as possible by following these methods:
- Choose charts and graphs that suit your data
- Your visual should include a scale to give context to the data
- Baselines for data should always start at zero
- Both axes should appear in the graphic and be equal in size
- Use all relevant data in the visual; don’t leave important data out
Size plays a major factor in trust-building—use similar-sized visual elements, like icons, that can be scaled on a graph.
Show changes in data through size and space but both should be equal between all visual elements.
Keep visualizations simple
Pulling together data requires a great deal of time and effort. It can be tempting to design visuals that express as much information as possible.
But that mindset can negate the effectiveness of visually representing data, and overwhelm your audience.
Visualizations should be simple and easy to understand—not only is this a brand design trend in 2021, but it keeps readers more engaged, like this chart we created.
While a complex visualization may look sophisticated and interesting, if your audience spends too much time trying to understand it, they’re going to eventually give up and move on.
A badly-designed graphic, like the one below, will also give readers a negative impression of your brand and product, losing you more potential customers.
Data graphics should be simple enough to understand at a glance—that’s all the time you have to get users’ attention.
Don’t overuse text
If your data story needs more text to understand it, the visual isn’t well-designed. While there needs to be some text in the graphic, it shouldn’t dominate the image.
You can always write a blog or social media post around your findings, but your readers shouldn’t be lost without the context.
The benefits of data-driven storytelling lie in the fact that your information can be communicated through the visual medium.
If you’re relying on text to do all the talking, your graphic is lacking. Use graphic elements like icons and shapes, and break your data down into bite-sized portions so it’s easy to convey.
Use colors wisely in visualizations
Colors have a lot to do with the importance of data visualization storytelling—they can be used to highlight key information in a graphic and augment the data story you are trying to tell.
But that doesn’t mean you use all the colors in the palette in your graphic. Again, too many colors, like too much information, can overwhelm the audience.
On the flip side, by using too few colors, you can mistakenly create connections between data that aren’t correct.
Use your brand colors in your visualizations, and augment them with two or three colors. Try not to exceed five colors or five hues of a single color.
If you’re wondering what kinds of colors work together, you can use this list to choose color combinations.
Use muted colors in your graphics, instead of bold ones, as that is what is on-trend at the moment and will make your visuals more relevant to audiences.
Highlight data in visuals
As much as you want users to understand the data as you present it to them in a visual, you aim to capture their attention as quickly as possible.
Even the simplest visuals need some highlights to draw the eye and it’s a great way to maintain the integrity of your data story.
Use a highlight color to make relevant data stand out or increase the font size or icon size to do the same.
By spotlighting the most important information, you will be more successful in attracting attention to your visual and telling your data story.
Businesses can leverage the importance of data storytelling
We’ve highlighted how data storytelling can make a difference in business growth in 2021.
Graphics share insights and correlations that audiences may have overlooked, while still being compelling tools that engage and convert customers.
The post Unlocking the secrets of data storytelling in 2021 appeared first on Search Engine Watch.
Today, Data Studio users can access over 300 data sets in just a couple clicks. From Google Ads to BigQuery to your CRM data, you can spend more time finding and sharing insights and less time configuring data sources. With two brand new data connectors you can access even more data through Data Studio to help you analyze your marketing investments and make decisions. You can now access your market research data with our new Google Surveys connector and connect to the next generation of Google Analytics with support for Google Analytics 4 properties.
Google Surveys give you a quick, cost-effective way to get valuable insights into the minds of your target audience. Gather the insights you need to make smarter, faster business decisions—in a fraction of the time it takes for traditional market research. With the new Data Studio integration, you can quickly visualize your Surveys data alongside your marketing data from sources like Google Ads and Google Analytics.
We’ve made it easy to visualize your Google Surveys data. Simply click “View report in Data Studio” when you’re in Google Surveys to see your survey data in a template that you can customize and share in a couple clicks.
In addition to expanding access to Google Surveys, we’re also excited to announce support for Google Analytics 4 properties. You can now connect to your Google Analytics 4 properties in Data Studio along with your Universal Analytics properties.
Accessing the data you need to make better decisions is only the first step. Finding insights from the data and determining the best way to communicate the insights to stakeholders can be challenging and time consuming. We’re making it easier to get started with new marketing templates across common data sets like Google Ads, Search Ads 360 and more. You can find over 30 solutions to help you get started in the Data Studio gallery.
We are excited to hear how these new data connections and template solutions help you find insights and make decisions. Drop us a line in our community forum to let us know what’s working well and what you’re excited for next.
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