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Headless CMS: The Solution to Top Challenges in Ecommerce

Sun, Feb 07 2021, Charles Dickens

In a rapidly evolving environment with technology and content demands existing in a multi-channel—and devices—world, Marketers in ecommerce face many unique hurdles that are both challenging and exciting—but can be very stressful.

In conversations in the last few years with prospects, most retail organizations believe they lag behind their competitors when it comes to marketing performance and managing the right CMS technology (web content management system). We often see these three common problems that online retailers face today:

  1. Large number of SKUs. The number of SKUs and configurations retailers manage can easily reach hundreds of thousands or even millions of options.
  2. Breakneck speed promotions. Working at a breakneck speed with weekly sales, promos, and campaigns in between major sales events like Black Friday.
  3. Juggling different content. Handling multiple, unique sales events and projects, all with varying content, different phases and timelines.

Traditional CMS in Retail

In a traditional CMS, you have to set up many individual installations and, they are all siloed on their own database/infrastructure. Migrating content and pages from one instance to another is often a manual process, or you’ve maybe spent the time and money to automate it with scripts and other technologies that have to be constantly maintained.

Headless CMS in Retail

With Headless CMS, all of your company’s content is stored centrally. You set up one installation for content and then different "view" for each project.

Unfortunately, most Headless CMS solutions have only two “views” (APIs) to access content – preview and production.

“Preview” will deliver all content for all projects in the same view whether it’s ready for testing, and regardless of whether the content is relevant to this week’s or next week’s project. “Production” will show all live content, regardless of where you want it to appear. This can make it a nightmare to properly test and stage content each week.

For example, every week you may have sales, ads, and related content to set up and stage. test next week’s promotions if in the same view, you also saw the discounts queued for the week after and some of the marketing content for the upcoming Black Friday sales event.

The Solution – Project Spaces with SampleSite

SampleSite solves this by supporting as many project spaces as needed. You can create a project space for each individual event and deliver only the relevant content.

For example, you may have three discounts to set up: one for next week, one for the week after, and a third that spans both weeks. A CMS solution like SampleSite lets businesses create a project view for each testing before the promotions even begin.

An added advantage to this approach is that you can easily update the discount and roll it out to both weeks when you need to change it.

Related Post

Data Mining and its significance in Business Analytics

We have always heard people in the business world say how data is valuable and must be secured. But, data generated by a single organization is so much that it would be impossible for a team of humans to filter out the essential data from tons of raw data. Here is how data mining comes into the picture. Data mining is a process that organizations use to turn raw data into useful information. Organizations utilize software to analyze large sets of raw data and look for patterns. These patterns help organizations learn more about their customers or even the general public.

This information pulled out helps to improve the decision-making process. Thus, strategies to increase sales, market, and deploy upcoming features are further apparent. Data mining is an indispensable part of any organization's intelligence. It helps perceive valuable insights by identifying patterns in raw data, thus turning them into useful information. 

Frequently data mining is confused with terms like machine learning and data analysis but, these terms are very different and unique. Data mining and machine learning both use patterns and analytics. Data mining looks for patterns that are already present in data. Patterns bought to light by data mining need human intervention to make decisions. Data mining gets patterns (information) from large datasets, and data analytics is when organizations decide to take this information and dive into it to learn more.

Businesses that make use of data mining have an advantage. They have a better understanding of their customers, oversight of business operations, improved customer acquisition, and new business opportunities. Also, they acquire a perception of potential customers, new ways to market and improve their systems. Data mining helps businesses advance without any obstacles. 

Data mining helps organizations with the detection of fraudulent activity and forestall potential fraud. Instead of relying only on the human experience, patterns generated from data mining can help you make a creative and innovative decision, one which might be beyond human analysis.

The future of business with AI

"Intelligence is not a skill itself, it's not what you can do, it's how well and how efficiently you can learn new things."
Artificial intelligence (AI) is advancing out of research labs and into the business world. Its power is being harnessed by leading companies across numerous industries — from banks examining countless data points in seconds to detect fraud, to call centers deploying chatbots to enhance customer interactions.
The recognition of AI in mainstream society might be a new phenomenon, but, it is not a new concept. The field of artificial intelligence came into existence in the year 1956. It took decades of effort to make notable progress in developing an AI system to make it a technological reality. In the business world, artificial intelligence has extensive uses. Most of us daily interact with an artificially intelligent system.
Artificial intelligence is not a replacement for human intelligence, instead, it is a support system. Although AI might not be good at completing simple tasks, it is skilled at processing and analyzing huge sets of data as compared to a human brain. Due to this quick process, business leaders with the help of AI can effectively resolve problems and take prompt decisions.
Artificial intelligence is kind of the second coming of software," said Amir Husain, founder, and CEO of machine learning company SparkCognition. "It's a form of software that makes decisions on its own, that's able to act even in situations not foreseen by the programmers. Artificial intelligence has a wider latitude of decision-making ability as opposed to traditional software."
These traits make artificial intelligence extremely valuable throughout many industries. Artificial intelligence is a vital associate when it comes to looking for loopholes in computer network defenses. With the escalating complexity of cyberattacks, cybersecurity specialists require additional assistance and this where AI is playing a significant role. Perhaps the most superior tool developed might be AI, but just like everything else, it can have useful as well as unfavorable consequences. If AI can be put to use responsibly, transparently, and justly, it would be a boon for businesses advancing towards growth and building a better world.