Often times when we are creating an application, the data we use determines what we show to the user. For example, in a to-do application, we may have multiple to-do list items. In Vue, it is easy to display multiple data points through the v-for attribute in our Vue templates.
Let’s suppose we have some data we are storing on a single page component. Our .vue document looks a bit like this:
Mulesoft DataWeave is a simple powerful tool to transform data inside a flow. Numerous core operators and functions are already present to perform various operations such as capitalize, camelize, upper, and lower.
For string operations, there are no core functions present to resolve a wildcard. I hope the DataWeave(DWL 1.0) function below helps you to perform a requirement where you want to resolve a wildcard using a set of parameters.
Working with data, there are several scenarios to transform data from input files using the Mule 4 connector.
There are several scenarios for files with special characters or language-based characters.
MySQL semi-synchronous is a plugin mechanism on top of asynchronous replication that can offer better durability and even consistency. It helps in high availability solutions, but can in itself reduce availability. In this article, we will look at some basics and follow up to present scenarios requiring higher-level intervention to ensure availability and avoid split-brains.
As a quick recap, semi-synchronous replication is a mechanism where a commit on the primary does not apply the change onto the internal table data and does not respond to the user until the changelog is guaranteed to have been persisted (though not necessarily applied) on a preconfigured number of replicas. We limit our discussion to MySQL 5.7 or equivalent.
The email channel is known for multiple advantages. It is convenient to implement practically, offers many options, and has a fantastic ROI of up to 4200%.
But we also face problems, the most disappointing of which is people ignore emails, not performing the desired action, or worst of all unsubscribing. Why does it happen?
The web is constantly progressing. It offers many tools like modern HTML template builders, ESP services, and other digital assistants that help us at all stages. But even the best tools are not enough; the secret of success still rests with us.
In this post we’ll cover the 7 cardinal sins of email marketing, to help you avoid them.
I can define this mistake as probably the worst. It’s worse than broken links, incorrect dates, or prices. Even more harmful than ugly design.
We lose a lot when postponing email strategy implementation. Beginners often focus all their attention on the content, social media activities, SEO issues… All that is important, right. But ignoring email campaigns is a hard fail.
Thousands of visitors never come again to your website. In other words, they leave the very first levels of the marketing funnel. While regular emailing keeps them engaged and prevents churn.
So delays here are only profitable for competitors. Don’t wait until you collect “enough” contacts. Start as soon as possible.
Frequency matters too. Don’t bomb people with emails; it annoys and causes unsubscribes. Email frequency is an individual parameter depending on many factors.
A fundamental axiom: people unsubscribe when emails are irrelevant. The same goes for neglected expectations. Even the best content with next-gen features won’t save the situation.
I mentioned the email frequency a bit above. Notice that if you announce the weekly emails but send them every day, this is an example of ignoring expectations. Be honest with readers.
Another typical issue is off-topic. If your subscribers are waiting for content related to smartphones, send them newsletters about smartphones, not dresses or domestic turtles :)
But in some cases, getting off-topic can be good. It all depends on the target audience, actual situation, and communication style.
Once again, relevance is vital. So we must avoid generic emails. Instead, especially if your contact list is extensive enough, apply all the possible parameters: age, gender, location, customers history, etc.
Where to get the respective data? A typical solution is to use update preferences forms in emails or on the website. Let clients choose the topics that are interesting for them.
Use surveys, sign-in forms, AI-based techniques of segmentation… Smart algorithms are great helpers that track clients’ behavior and then process the data for segmentation purposes.
The better we know our subscribers, the deeper we segment the contact list. It allows sending precisely targeted newsletters to respective segments.
As Hubspot stats say, personalized emails’ open rate is 26% higher, and their click-through rate is 14% better. But even besides index data, poor personalization is just nonsense today.
Clients are looking for content that matches their preferences, so marketers have to consider these expectations. Segmentation and dynamic range are essential here, but they are not the only techniques.
Everything is much more sophisticated here, in addition to personalized subjects and content. Another solution is to generate recommendations that include the previously browsed products.
AI-powered automation comes to help. Machines will upgrade the classical personalization to the next level called hyper-personalization.
It’s simply unacceptable to send non-responsive emails today. With so many people opening email on different devices, this is a huge fail.
The modern world is full of gadgets and devices. Email has been opened on smartphones more frequently than on desktop PCs and notebooks in recent years. Up to 70% of readers will read messages on mobiles very soon. No wonder that responsivity turned into a mobile priority.
Regarding layout and design, there are no problems: modern template editors are featured with automated responsivity. But mobile-first means not only layout/design adjustment for mobiles, full-width buttons, or larger fonts. We have to work with content too. Don’t overwrite text remember that recipients read inbox emails on the run.
Just imagine yourself reading emails in the cafe or cab. And ask yourself: is everything convenient? Would you take the desired action on the run?
People are quite skeptical of new brands. We need to do our best to attract them. So everything must be done professionally.
The best solution: be a perfectionist. If newsletters look amateurish, they are likely to repel.
Being amateurish will also ruin your brand identity and reduce customers’ trust. Pay close attention to design, stick to your corporate style, analyze each detail in the context of overall harmony.
Testing is vital. Before sending an email campaign, check it via Litmus or Email on Acid to be sure that message looks just as planned. These tools allow testing email rendering by +90 combinations of email clients, devices, and OS.
Knowledge is power. Always try and test your marketing strategies. Are you satisfied with your actual performance? Run A/B tests and focus on the most significant wins and failures.
Of course, threats are not limited to these seven failures. The last piece of advice: never ignore trends.
Accessibility? Don’t forget about clients with special requirements. Get whitelisted and incorporate these technologies in your campaigns.
And constantly strive for perfection. With this doctrine, you’ll win!
Featured image via Pexels.
The post 7 Worst Fails in Email Marketing first appeared on Webdesigner Depot.
Data junkies rejoice, this is the episode for you.
On this week’s episode of Dev Interrupted, Einat Orr, co-founder and CEO of Treeverse, sits down with us to talk about the state of data… where it’s been, where it’s going and why having bad data might be worse than having no data at all.
The popularity of web scraping is growing at such an accelerated pace these days. Nowadays, not everyone has technical knowledge of web scraping and they use APIs like news API to fetch news, blog APIs to fetch blog-related data, etc.
As web scraping is growing, it would be almost impossible not to get cross answers when the big question arises: is it legal?
At its core Snowflake is a data platform. It’s not specifically based on any cloud service which means it can run any of the major cloud providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). As a SaaS (Software-as-a-Service) solution, it helps organizations consolidate data from different sources into a central repository for analytics purposes to help solve Business Intelligence use cases.
Once data is loaded into Snowflake, data scientists, engineers, and analysts can use business logic to transform and model that data in a way that makes sense for their company. With Snowflake users can easily query data using simple SQL. This information is then used to power reports and dashboards so business stakeholders can make key decisions based on relevant insights.
Private, public, or hybrid, cloud solutions for any business domain are designed to provide the freedom to grow and security for the organization and customer data. For cloud-based multimedia solutions, there is cloud-based custom transcoder IP that supports automated Video-On-Demand (VOD) pipelines. Cloud services offer solutions that ingest source videos, processes video for playback on a wide range of devices using cloud media converter, and store transcoded media files for on-demand delivery to end-users.
Custom IP integration along with other cloud services showcases better feasibility of using Open-Source codec, to use one’s transcoder instead of cloud media-converter for multimedia solutions. In this blog, we will see how an Open-Source codec like AV1 is selected as a custom IP for encoding to integrate over the cloud as a service.
Dealing with a database is one of the biggest challenges within a software architecture. In addition to choosing one of several options on the market, it is necessary to consider the persistence integrations. The purpose of this article is to show some of these patterns and learn about a new specification proposal, Jakarta Data, which aims to make life easier for developers with Java.
Whenever we talk about complexity in a corporate system, we focus on the ancient Roman military strategy: divide and conquer or divide et impera. To simplify the whole, we break it down into small units.
