Author: Franz Malten Buemann

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If you want to generate leads, it’s important that you bring in a lot of traffic to your site. To make the most of your website, you need to identify the top traffic sources that provide your business with the leads it needs. In this blog post, we’ll break down the most important lead sources:…
The post Where Are Your Leads Coming From? Breaking Down Lead Sources appeared first on Benchmark Email.

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Heyoo ✌🏼! Our website’s landing page just got a facelift, and I was in charge of the messaging. It’s my first time leading the charge on a landing page, so I’d love to get some very honest feedback to see how we did. I’m most interested in the clarity of our messaging. Is it clear what problem we solve, why it matters, and how we do it? After reading through the landing page, what do you understand Beyond is offering? I would really appreciate your feedback so that we can improve and iterate. Thanks a ton in advance! Here’s the landing page: https://beyond.so/ submitted by /u/drniklas [link] [comments]

 

 

Successful development of any activity requires effective and precise performance measurement. Surprisingly various researches and surveys point out that eCommerce marketers find their abilities in this matter lacking. In this article we will explore 4 problems and trends related to performance measurement – and point to solutions that will make your marketing stack futureproof.

 

The confusing lack of abilities

 

Marketing teams in eCommerce need various datasets to effectively track the performance of their stores.  Sadly, the toolset providing this data is fragmented and, as a result, cannot provide the marketers with a complete performance overview. This results in problems, diagnosed by many analysts: 

89% of marketers ranked improving the ability to measure and analyze marketing impact as a top priority (Responsify), Only 58% of marketers say they are often successful in achieving their marketing goals (Responsify), Only 29% of marketers said they had no issues or delays in getting results from automated campaigns (VentureBeat). By 2025, data stories will be the most common way to use analytics, with 75% of data stories automatically generated rather than made by data analysts. (Gartner) 

 

4 Statistics That Will Prove The Importance Of The Performance Measurement

 

These problems and challenges require immediate addressing. We took a closer at the research behind the statistics, pinpointed its most important aspects from the marketers point of view and – last but not least – provided some hint about how to futureproof your marketing.

 

89% of marketers ranked improving the ability to measure and analyze marketing impact as a top priority

 

Receiving analytics is not all complicated. Registering the impact from your analytics and being able to set forth and become proactive in capitalizing on those insights is an important factor that is generally looked over.

 

The Research

 

In 2017 Demand Generation Benchmark Survey Report “Increased Pipeline Influence Ups The Ante On Attribution, Reporting and Measurement” conducted by Demand Gen, indicated that 89% of marketers perceive improving the ability to measure and analyze marketing impact as a top priority. In the survey “Tapping Multichannel Marketing & Data As Key Engines for Growth” conducted a year later by the same company, 61% of respondents ranked improving the ability to measure and analyze marketing impact as top priority.

 

The Importance

 

The fact marketers need to measure impact of their efforts is by no means any wonder. After all it is absolutely fundamental to prove the revenue contribution to the CEO, not to mention that any improvement requires data to scale. What surprises, is the fact, that in the apparent abundance of measurement tools marketers still feel the need to improve. This indicates marketers need a single source of unified, viable information. 

 

How to future-proof your marketing?

 

This can easily be solved with the feature integrating data representing online store performance in a similar way Customer Data Platform integrates all the customer data into a unified 360 customer profile. In such a case, data like transaction value, number of items purchased or average order value must be easily accessible for the marketer. Another information you will absolutely need to be presented by the feature is contact and visit analytics as well as centralized view on KPI’s. However, what will really enable you to get a grip on the business on the fly is top-tier revenue attribution, for both channels and tools. Such a view will clearly show you which channels are excelling and which you should drop, or on the contrary – invest more effort to make them effective. This is what we live Omnichannel Growth Intelligence.

 

marketing revenue attribution

 

Only 58% of marketers say they are often successful in achieving their marketing goals

 

The Research

 

CoSchedule’s 2022 Trend Report on Marketing Strategy uncovers how successful marketers around the world work. There can be many factors and reasons for this, but when put into the context of the statistic analyzed above, one may wonder, how it happened, that this many marketers are actually often successful.

 

The Importance

 

Marketers struggle with lack of insight into the effects of their own actions. These actions very often bring immediate results, but, in the absence of relevant monitoring tools, most of them slip under the radar, leaving marketers clueless and confused.

 

How to future-proof your marketing?

 

The effective solution would require at-a-glance, live overview of online store’s performance, accessible 24/7. This would allow them to: 

Immediately identify hot areas Locate the most critical performance indicators Gain an in-depth analysis of eCommerce environment. Efficiently streamline workflows, re-allocate resources and make more informed strategic decisions.

 

Store’s performance overview

 

So minimizing delays and errors seems crucial – which leads to the next statistic.

 

Only 29% of marketers said they had no issues or delays in getting results from automated campaigns

 

The Research

 

In 2015, Venturebeat decided to answer a trubling question. In their recent report on marketing automation they found out that companies adopting Marketing Automation tools are generating outsized leads, conversions, and revenue — so why have only 5 percent of businesses done so?

 

The Importance

 

Turns out that such tools are often complicated to implement. Data provided by eCommerce platforms and Marketing software can be disjointed and cause a gap in understanding customer behavior and their journey. Without real-time comprehensive data, there’s a lack of insight that would allow businesses to make smart decisions. To bridge this gap and gain a holistic view, marketers often use Google Tag Manager as a popular choice. Another popular choice is Digital Marketing Platforms. They have the advantage over GA that they also measure not only website visits, but also email OR, CTR, offline transactions and more. These differences are especially noticeable with the free version of Google Analytics.

 

How to future-proof your marketing?

 

Using dashboards with clearly visualized data from both eCommerce and Marketing platforms helps you bridge the gap between the two and minimize the risk of incorrectly linking events in the store. This makes it easier to gain a better grip on business activities, giving you the ability to access your data live 24/7. As a result, with this more comprehensive view of the store and its operations, you can make better decisions while optimizing marketing strategies, leading to greater ROI.

 

Events on the website in real time, at-a-glance

 

Integrated data from various sources

 

Did I mention “beautifully visualized”? Let’s move a bit into the future.

 

By 2025, data stories will be the most common way to use analytics, with 75% of data stories automatically generated rather than made by data analysts

 

The Research

 

According to Gartner, data storytelling will become a prevalent method of consuming analytics by 2025. They go even further, claiming that by then a full 75% of data stories will be automatically generated using augmented intelligence and machine learning rather than generated by data analysts.

James Richardson, a research director at Gartner who spoke on Feb. 24 2021 during a virtual conference hosted by data storytelling vendor Narrative Science, claimed that “It is an inevitability that we move to far higher levels of automation in analytics and that we move away from the current dominant self-service model,”. He also said that “The self-service and visual paradigm that now dominates BI is a limiting factor. It’s only as good as the individual’s ability to serve themselves.”

 

The Importance

 

And why is it really, really important to marketers? Because, as Gartner states, you probably don’t use analytics enough. As they claim “Depending on the source, it’s estimated that only about 30% of employees in most organizations use analytics as part of their jobs. And despite advances in augmented intelligence and vendors’ emphasis on ease of use to try to make analytics accessible to more users, that percentage has become stalled.”

 

How to future-proof your marketing?

 

Now, clearly visualized data is not exactly data storytelling yet. But this is a step in the same direction; to make data digestible to the point of being actually usable by someone other than data scientists. And on a daily basis, at-a-glance, 24/7.

So take all the kinds, types and sources of data we mentioned in this article and visualize them in a compact, easy to grasp overview and you have your almost perfect dashboard for eCommerce. Almost, because to reach perfection, a few steps towards data storytelling are needed.

Take the example of loyalty building. The term seems too complex to be be simply put on the screen. However, if treated as a derivative of crucial KPI’s, it is perfectly possible not only to visualize, but to monitor in real time. Paired with omnichannel revenue attribution and other data, this will enable you to work on customer loyalty, and even Customer Intimacy, live, on the fly.

 

Loyalty building dashboard

 

Wrap up data analysis and performance measurement

 

The problem surfaces, as more and more agencies research the topic of data analysis and performance. When it comes to efficiency, data-based decision making is crucial, and abundance – as well as disjointment – of data becomes more curse than blessing.

While data storytelling will find its way to the average marketers desktop eventually, what you need now, is a direct answer to the presented findings that:

delivers unified, relevant performance datamakes it accessible at-a-glance, live, 24/7visualizes them, so they can be usable by all company’s employeesenables to track and enhance even detailed data like omnichannel revenue attribution or the effects of loyalty building efforts.

Which is exactly what modern martech software, specifically Customer Data Platform, with comprehensive eCommerce Dashboard, is being created for.  If you check such an actual release for yourself  read this article. 

Hello friends, I’m amazed by how powerful OpenAI is. This post is a combination of both information and promotion, so please bear with me. One of my friends is a freelance writer and he has to consistently create new content for his clients. He wanted a fast and efficient way to leverage AI into his workflow. Without having to go to ChatGPT or OpenAI playground in a separate browser window and do a bunch of copy-paste work. He wanted the power of AI right in his daily use apps like Notes and Google docs right into his Mac. So I added a few features in my Mac app that can let him do this. Features like “Rewrite” in “Professional” or “Friendly” modes. And “Generate Blog Ideas”, “Outline Blog” etc. He shared a few screenshots of how he uses the app – Changing the tone of his writing – ​ https://preview.redd.it/wkzm02dhkxka1.png?width=2000&format=png&auto=webp&s=91cbc6e3f2c76052ef651a5fda95a49b57042093 Generating blog ideas – ​ https://preview.redd.it/ehk4d3cjkxka1.png?width=2000&format=png&auto=webp&s=eee69b86a9f9dbbd1e4971b8d531ddd79f7cd24a He’s using the app as a starting point when starts on a new article, works with it throughout the writing process, edits and polishes the content, and finally hits publish. He’s using AI more as a “writing partner/assistant” and not as a complete replacement for his writing. I think this is a better use case for AI in the long term. Do let me know what you think. You can try out the app for free for 30 days from this link – Elephas Do share your feedback. I’d be happy to add new features and utilities based on your requests and suggestions. Thanks submitted by /u/juliarmg [link] [comments]

Artificial intelligence is getting a lot of traction in the marketing world. According to Statista, 80% of industry experts integrate some form of AI into their online marketing activities.
However, if you’re like me and are unfamiliar with AI beyond what you’ve seen in science fiction stories like I, Robot or Black Mirror — you’re probably wondering what AI is and how to use it in marketing.
Is AI really what it looks like in the movies? This article will explore the definition of AI, the different types of AI, and how AI can improve marketing processes.
What is artificial intelligence?
How does AI work?
What are the four types of artificial intelligence?
How Marketers Can Use AI
The Pros and Cons of AI
The Future of AI in Marketing

So now you know what AI is, let’s explore how it functions.

How does AI work?
AI combines large sets of data with intelligent, repetitive processing algorithms to learn from patterns and features within the data being analyzed. The AI continuously processes and learns from the data.
Within each round of data processing, the AI system tests and measures its own performance to gain additional expertise.
AI can run through thousands, even millions, of tasks repeatedly — improving its performance in a short amount of time. However, there are multiple kinds of AI, each with its capabilities and limitations.

What are the four types of artificial intelligence?
The four types of artificial intelligence are reactive, limited memory, theory of mind, and self-awareness.
Reactive
A reactive AI can only use its intelligence to react and reply to the world around it. It can’t store memory; therefore, it can’t rely on past experiences to inform real-time decision-making or problem-solving.
Reactive machines can only complete a finite amount of specialized tasks. Though this may sound like a drawback, it has its perks. A reactive AI will react the same way to the same stimuli every time — making it reliable and trustworthy.
One of the most famous examples of reactive AI is Deep Blue, a supercomputer created by IMB in the 1990s that won a chess match against chess champion Garry Kasparov. Deep Blue could identify the chess board pieces and how each piece could move based on the game’s rules.
However, the AI could not try to anticipate its opponent’s next move, nor could it think of ways to put its piece in a better position.
Limited Memory
Limited memory AI stores previous data and predictions and uses it for decision-making — looking into past data to predict the future. Limited memory AI is when a machine learning model is continuously trained to analyze and use new data.
Limited-memory AI consists of six steps to follow.

Create the training data.
Create the machine learning model.
Enable the model to make predictions.
Have the model receive human or environmental feedback.
Store the feedback as data.
Repeat all the above steps in a cycle.

Examples of limited memory AI are self-driving cars. Self-driving cars identify civilians crossing the street, traffic signals, and other data to make better driving decisions and avoid future accidents.
Another example of limited memory AI is HubSpot’s adaptive testing tool. The adaptive testing feature splits traffic evenly between page variations at first.
As HubSpot learns how these variations are performing, we adjust the traffic automatically, so optimal-performing variations are shown more than the poorly-performing ones.
Theory of Mind
Theory of mind AI is as it sounds — theoretical. AI has not yet advanced to this type, so theory of mind is still in its innovation stage. This type of AI interacts with the thoughts and emotions of humans. Theory of mind will better understand the entities they interact with so they can understand their needs, beliefs, feelings, and thought processes.
For example, we now know that self-driving cars are a form of limited mind AI. If these autonomous cars could analyze and understand their drivers’ mental and emotional states to improve safety, they would evolve into Theory of Mind AI.
Self-awareness
Once theory of mind is a reality, the next type of AI to emerge will be self-awareness. At this point, machines won’t just be aware of humans’ emotions and mental states — they’ll also be aware of their own. A self-aware AI will have a human-like consciousness and understand its existence in the world and with others.

How Marketers Can Use AI
AI can perform parts of the marketing process — such as task automation, campaign personalization, and data analysis — so you can spend less on repetitive tasks and more on strategy.
For example, our HubSpot mobile app has a business card scanner that uses AI to pick out the name, email address, and other contact information on a business card and map them to your HubSpot properties. Instead of spending time manually entering this data yourself, the AI automates the process for you.

 

The Pros and Cons of AI
So, now you know what AI is, how it works, and the four types of AI — let’s get into the pros and cons of AI technology.
The Pros of Artificial Intelligence
Fewer errors
Humans can make mistakes, miss deadlines, misspell words, and get the math wrong. Sometimes we’re distracted or going through burnout; it’s human nature. By implementing an AI-ran automated system, you’re lessening the risk of errors.
24/7 Uptime
AI also doesn’t need rest and can run 24/7. AI’s can run constantly and consistently for as long as it’s programmed to. This makes AI more ideal than humans for repetitive tasks, allowing marketers and business owners to focus their efforts elsewhere.
Can analyze large data sets quickly
As I mentioned earlier, humans sometimes make mistakes — especially when processing large data sets. A solution would be to work slower to prevent errors, but time is money in marketing.
Fortunately, AI machines can quickly process large amounts of information and data, making them more efficient than humans in a deadline crunch.
The Cons of Artificial Intelligence
Lack of creativity
AI is programmed to react to stimuli based solely on data from the past, meaning they’re not currently suitable for creating innovative solutions. Data from the past can help predict future outcomes, but data alone isn’t always enough to address a never-before-seen variable.
Therefore, AI would be better suited for “grunt” or mundane work. From a marketing perspective, humans can develop a creative marketing strategy, while AI can take care of the repetitive tasks that implement the plan.
Impersonal
Sometimes, human connection is the best way to forge a closer relationship with your audience. While a self-aware AI is possible in the future, current AI machines cannot perfectly mimic the human experience.
From a marketing perspective, implementing AI in every customer interaction can create a rift between you and your audience. I mean, there’s a reason many of us can recall shouting, “speak to a representative!” when we’re tired of speaking to a robot on the phone.

The Future of AI in Marketing
According to Grand View Research, the global AI market is expected to reach $1,811.8 billion by 2030, up from $136.6 billion in 2022.
Artificial intelligence, theory of mind, and self-aware machines all sound like things from a distant future. Still, the reality is AI is here now, and its impact across industries will likely grow in the years to come.
While AI has pros and cons, it’s important marketers stay tuned in to its advancements and be open to using AI to streamline certain processes to keep up with competitors.