Black Friday retailers must be effective, ready, and resilient

Retailers on Black Friday must be efficient, ready, and flexible

The problem is to implement personalized, search, and tailored offers to maximize conversion rates while avoiding booms.

An unprecedented Black Friday is approaching. Will consumers hide their faces back to stores and clean up store shelves? Only if you have promotion about Clorox sanitary chopstick loader. Will they flood your app or website? Perhaps.

As one data scientist put it, “All predictions are wrong. Some are lucky”.

Some retailers are likely to continue to see demand drop even on Black Friday – such as those that specialize in men’s slit pants. Most retailers have seen their traffic turn online. For this Black Friday, they need to operate efficiently, ready, resilient, and cost-effective.

Efficiency is the conversion rate of visitors to buyers. Readiness is measured through through through through meter and latency, even when there is more than one traffic at a time. Resilient is handling whatever 2020 throws at it. Finally, in the cloud age, cost-effectiveness is corroding the world. (I feel that eye 40.)

Retailers on Black Friday must be efficient, ready, and flexible
Retailers on Black Friday must be efficient, ready, and flexible

Effective home page
The front page needs to be sold to be effective. Any site analytics will tell you that the most visited page is the homepage. Analytics will also tell you that the homepage has the highest bounce rate. In order for the front page to be useful, its content needs to be contextual.

Customers returning to your front page are often the easiest to convert. They didn’t come to your site through paid-per-click ads, searches, or referrals. They come directly to your site because they know you. When they arrive at the homepage, it’s not just any promotions or set of items. It must be incentives designed specifically for that customer.

For first-time visitors who arrive to receive offers or through other referrals, the homepage should also be customized. Artificial intelligence, machine learning, or just old counting will merely calculate other items that have been purchased by people who have accessed that offer. If the offer is completely new (a cold start), use data from existing customers who clicked on the order.

For first-time customers who come to the homepage without context, the page is also not static. As the day goes by, the content rotates based on what people are buying or looking for. In addition, the front page should provide shoppers with this first time to encourage them to identify themselves.

Search for performance
The straight search keyword is dead. As a regular customer, if I enter “shoes”, the search will know that I do not want to talk about high heels. My client profile and my past searches will inform my search results. I should have a way out of this personalization by being more specific, but if I enter “shoes,” I’ll see running shoes and flip-flops, based on my previous purchases.

While the site may not know first-time shoppers’ interests, context will inform future searches. This means that if I enter “skis” and go to “joggers” and then “boots,” I’ll see snow boots and ski boots, not cowboy boots.

There are many tools to personalize search and homepage. Some commercial platforms like BigCommerce or Shopify have many of these features built-in. Third-party providers such as Coveo and Lucidworks provide solutions for this type of signal capture and personal machine chemistry.

Recommended effectiveness
Exclusively for you, we are giving you a 20% discount on de-freezing equipment. Seriously, I’ve got suppliers offering me defuze equipment for all the icy winters that we get here in Savannah, GA. Context and personalization make attractive offers. If I search for something, click on it and start leaving the site, then the smart way to play is to give me something similar or a discount on what I’m watching.

As a result, if I searched for some related items such as glass cups, tubes, malts, and hops, I would probably be offered a package such as a home beer starter or the most popular beer-making item.

No problem, the offers must be personal (Who am I? What do I like?) And contextual (What else did I search for? I’m leaving, looking for something else, buying something?). Many tools implement this type of personalized offer, including tools built into commerce sets. There are other third-party services such as that of Justuno or Privy.

Willing and resilient
By 2020, retailers should use cloud computing, which has a resilient architecture, and lives beneficially. Most retailers have moved their core infrastructure to the cloud. Ideally, this should be a commercial platform or a combination of SaaS and cloud-based solutions.

Content delivery networks (CDN) such as Akamai, Cloudflare or Netlify have been in existence for decades. Images, static content, and other resources can easily be cached at the edge of the network to reduce the load on your web server. Even five years ago, CDN was a luxury for kings or at least the Fortune 500. Today, they are affordable for the rest of us and there is no good reason not to use them for a modern website.

The next step is to ensure that the site’s database architecture and search are resilient and resilient. While most e-commerce platforms include search, these search engines may not scale when all personalization tools are turned on. Other solutions may need to be investigated. Those solutions should be replicated and there are several ways to scale up and fail gracefully. In short, they should have a modern cluster architecture. There are still many e-commerce sites that use search technology for decades, especially Endeca. These tools are not designed for modern or cloud traffic.

For databases, retail is often “over-provisioned”. A NoSQL database that can loosen consistency will meet the needs of most retail use cases. This means that you don’t need to pay for a distributed transaction unless the specific use case requires it. Almost any NoSQL database can be copied to multiple data centers and provide sufficient availability.

My recommendation is to select a multi-model database that enables quick collection of low latency signal data, retrieval of product data, and running real-time analytical queries. There are cloud service provider products such as Microsoft’s CosmosDB and third-party provider products such as Couchbase. Alternatively, you can combine several different databases together, but that involves paying more for ETL and handling higher complexity.

Cost savings
Even for retailers with more traffic, profit margins are under strain, so no one wants to pay for capacity they don’t use. The term “automatic rate change” is over-used and prolonged. Ask any provider (be it a database, search, or otherwise) and they’ll let you know that they can scale. But what happens when you want to reduce the number of instances you’re using? Can that happen without outages or excessive performance reductions? A lot of technology is scaled up. More will be scaled up.

The questions to ask are “Can I easily remove the nodes?” and “How often does it take to rebalance my data type and load?” You should also ask, “Can I turn off components that I don’t use?” and “How much does the idle cost of the software just run?”

Booming pop fizzle
It’s 2020. Suppose that anything can happen. Everything seems to be exploding, unstable or breaking out every day. This year’s deposit is higher. They asked to invest more imagination in “What could happen?”

What happens if your cloud service provider is unsuccessful in a target country? Multicloud is more than just a common word. For global retailers, it’s a necessity. There are geographical areas that cloud service providers prefer not to reach or where there is only one data center. A global retailer needs alternatives. You also can’t argue that your provider will never fail. While cloud service providers rarely fail compared to older self-hosted data centers, errors of many available domains are rare, it still happens. If it happens on Black Friday 2020 could be disastrous for some retailers.

Is the architecture of the site easily allowed to disable components or services that users do not recognize? What happens if your whizbang personalization component or third-party service is congested? It’s one thing if the homepage becomes more generic or doesn’t show the offer when exiting. It’s a bigger problem if the visitor sees 404 inside the iframe or receives an hourglass or spinning disc.

Keep it together
The great news about 2020 is that it’s coming to an end. Maintaining and converting customers on this Black Friday is fundamentally no different from previous years. If anything, there are more options. The only problem is to deploy personalized, search, and deliver fit to maximize conversion rates while ensuring the cloud-based structure can handle multiple errors while scaling to meet demand.

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