7 Steps to Building a Successful Customer Behavior Analytics Model

7 Steps to Building a Successful Customer Behavior Analytics Model

Having a comprehensive customer behavior analytics model is vital to ecommerce companies. Studies show that companies that use customer behavior information to their advantage outperform competitors by 85 percent in sales growth. Additionally, estimates show those who use behavior analytics beating competitors by an extra 25 percent in gross margins. The current influx of data available to measure customer behavior patterns is making it easier for ecommerce businesses to use analytics in the following ways:

  • Support core sales and marketing goals
  • Increase customer satisfaction rates
  • Improve product/service criteria
  • Optimize marketing channels
  • Make insightful improvements to overall sales strategies
  • Increase customer loyalty

Developing a customer behavior analytics model is vital to retail success for a variety of reasons, and ecommerce companies shouldn’t be without one. Read on to discover seven key ways to build the right customer behavior analytics model for your ecommerce business.

1. Use Detailed Data

As previously mentioned, there is an influx of big data in ecommerce businesses that help monitor customer behavior. Present analytics platforms can delve even deeper into consumer patterns, and tracking tools have become far more accurate. Estimates for the 2020 fiscal year suggest that ecommerce sales will pass over 4 trillion, and companies with a pulse on consumer behavior will take a larger chunk of those sales. The following forms of data can help retailers build a broad customer behavior analytics model:

  • Order tracking: includes buying patterns, most purchased products, and reordering habits
  • Consumer engagement: helps gauge what features, products, and information matters most to consumers
  • Changes in order patterns: helps businesses anticipate possible upcoming ordering changes that an online consumer may go through
  • Conversion rates: how many consumers convert from visitation to purchasing from a brand
  • Retention rates: how many consumers remain with a brand long-term
  • User feedback: customer satisfaction ratings, reviews, comments, and likes

The ultimate goal of using customer behavior analytics in retail is to get actionable insight into what consumers are looking for. Criteria for that can vary by company, which means the data needed can also vary; the list above gives forms of data that are useful to every ecommerce business. This is just a short list of ideas, and there are many forms of data that help ecommerce businesses build relevant models for customer behavior analytics. When determining what data to add, keep all major business specific KPIs in mind to get the best possible analysis of consumer behavior.

2. Throw Out the RFM Model

Use a life-time value (LTV) model instead of a recency, frequency, and monetary (RFM) model. Ecommerce businesses in particular benefit from using LTV over RFM. Digital tracking and an increase in the accuracy of analytics platforms has made RFM models a poor choice for customer behavior analytics. The reason they aren’t a good fit is because the majority of the key indicators for that model are based on immediate sales. They also primarily focus on those who spend the most money, and they lack any tangible insight into retaining new customers long-term. LTV models can provide actionable insight to take for individual consumers, target their long-term value to the ecommerce business, and select appropriate marketing for them.

3. Stop Making Assumptions Based on Age, Demographics, or Finances

There are 35-year-old people who watch cartoons, and believe it or not, that’s an excellent point of reference for this segment. Customer behavior isn’t measured by simply lumping age groups, demographics, or income levels into tidy piles and assuming what they will or will not respond to. Making assumptions about customer behavior patterns is not conducive to developing a successful or accurate customer behavior analytics model. The goal is to start thinking of customers as individuals, not groups. A 70-year-old can buy hiking gear and a 20-year-old may purchase knitting needles. To get the best possible results, find out what individual consumers want by basing analytics on real data and not assumptions. In short, don’t stereotype.

4. Use Predictive Analysis

Predictive analysis is an excellent way to draw in potential customers, keep existing customers, and anticipate future needs in order to suggest relevant products. Predictive analytics drive the following ecommerce metrics:

  • Customer acquisition: helps by tracking the consumer’s journey from the initial site visit to checkout to personalize their experience
  • Customer retention: helps by anticipating problem areas to repair based on data such as customer feedback or drop rates
  • Customer growth: helps retailers create calls to action based on ordering patterns during specific periods

Personalized advertising, suggestions, and promotions can all be tailored to customers using data obtained from predictive analysis. Using predictive analytics to understand the behavior of customers is another way to use big data in ecommerce to make changes that improve retention.

5. Know Your Goal and Create Steps to Reach It

Building a comprehensive customer behavior analytics model means knowing what goals your ecommerce company wants to achieve. There are many steps to building customer behavior analytics that companies can take advantage of to reach goals, including :

  • Set analytics goals and KPI’s, and track them
  • Determine critical paths, then break them up to get the most data
  • Set user properties to receive data on customers using your site
  • Continually monitor and adapt analytics models based on consumer practices and new data
  • Measure success of new products to determine their impact on sales
  • Use funnel analysis methods

Having specific goals in mind while developing customer behavior analytics helps ecommerce businesses make marketing and advertising decisions and changes based on reliable data.

6. Incorporate Funnel Analysis

Funnel analysis is particularly useful for determining abandonment rates through each stage of the checkout process. They also help establish the set of steps consumers must go through to reach any specific outcome on a website. Funnel analysis helps ecommerce organizations visualize data by showing drop off points. For this reason, these types of analytics are ideal for verifying drop rates, tracking site abandonment, and showing weaknesses that exist in each stage of the process. Funneling is also an excellent tool for ascertaining why conversions were unsuccessful.

7. Search Out Customer Access Points

Are you getting the most customer engagement from external or internal links? Are they accessing the site through social media posts or click ads? It’s important to pinpoint consumer access points for your brand and track behavior across all points. This type of behavioral analysis helps businesses target areas that produce the most clicks and conversions. That way, retailers can position ads appropriately to maximize their potential draw. Being able to allocate resources properly is one of the key benefits of analyzing consumer behaviors. For customer behavior analytics models to be successful, they have to include data from all areas of the business that consumers have access to. Access areas to include during the process of developing a customer behavior analytics model include:

  • Primary website: main ecommerce site
  • Apps: downloads, uninstalls, in-app purchases, and feedback
  • Social media: Facebook®, Twitter®, Instagram®, etc.
  • Click ads: any advertisement that provides a direct link to primary site
  • External links: links on other sites that direct users to primary site or other company resource

Metrics measurements should span across any location that gives users access to your brand, or they are not truly accurate. Using data from websites alone can give a lopsided view of customer behavior, because not everyone will access your product through the main site. It all circles back to the importance of analyzing customer behavior on an individual level.

The insight gained into the personal habits of customers is crucial to recommendation searches, email campaigns, and product suggestions. Do you have any insights into creating a successful customer behavior analytics model? Comment so readers can add them to the information they gained from this post. If you still need guidance on how meet your ecommerce consumer goals, contact eZdia where our professionals will be more than happy to help you succeed.

Author: Kristin Ann Hassel
Email: kristin.ann.hassel@gmail.com
Linkedin: https://www.linkedin.com/in/kristin-hassel-8651a3157

Product Description Word Count: How Much Is Enough?

Product Description Word Count: How Much Is Enough?

With 96% of Americans making online purchases in 2018, and 80% of those making at least one purchase in a month, you can see the importance of optimizing your product pages, and product descriptions are a key element. However hard you work on the rest of the page, if you get the product copy wrong, all the work you’ve put into the rest of the page is wasted. Bad product copy creates a bad user experience, and it doesn’t do well in the SERPs, either. How long a product description should be is just one of the many factors you need to consider when optimizing your product pages.

Just How Important Is Word Count for Product Descriptions?

Extremely. But it’s not as straightforward as “you must write 400 words for every product you carry”. It’s subtler. And there’s a number of things that contribute to the final decision regarding how long a product description should be. The key is to strike a balance between pleasing the Google Gods and creating the best user experience. There’s a marked difference between informative and engaging copy that gives the reader everything they need to know to make a buying decision, and padding a description with vague fluff and generic statements that add to the word count without adding value.

What to Consider When Determining How Long a Product Description Should Be

There’s no hard and fast rules for maximum or minimum word count for product descriptions, but here at eZdia, we’re experts in creating optimized product content that converts, so we’re sharing some of our key industry insights and guidance with you to help you win the content wars.

Type of Product

The type of product you’re selling is the main influencer that determines the length of your product descriptions. For example, a computer, large appliance, power tool, or electronic device requires a longer, more robust product description than apparel, simple tools, wires and connectors, kitchen accessories, or soft furnishings. When deciding how long your product descriptions should be, think about how many attributes, features, uses, benefits, and specifications your product has. If it doesn’t have many attributes or specifications outside of color and size, then you need a shorter word count. If your products are more complex, with lots of specs and features, then you need a longer description. You need enough words to convey all of the relevant information that the reader needs to make a purchase. If they have to leave your site to find more information on the product, they’ll buy from wherever it is they find the info they need. Depending on the client, their products, and their KPIs, we generally recommend 125-150 words for simple products like apparel, and 350-400 words for complex products like electronics and large appliances.

Using Bullets

Bullets are exceptionally effective when combined with a paragraph or more of product copy. Bulleted lists let you provide a rapidly scannable list of all the key features and specifications. They reduce overall wordcount, improve readability, and let your consumers quickly decide if the product might meet their needs, in which case, they can read your paragraph copy.

Using Feature/Benefit Structure

So many posts have been circulating the internet in recent years about only talking about benefits and ignoring the features. This is bad advice — and it just leads to vague, nonsensical waffle. It’s an over-simplified, distorted twist on the real best practices, to the extent that it’s moved beyond meaningless, into dangerous, because using the “benefits only” approach will harm your bottom line. Product descriptions that sell seamlessly combine features and benefits. Yes, people want to know how a product is going to help them and therefore why they should buy it, but they need the hard facts, too. It’s true that you need to keep the focus on the reader rather than the product, but you don’t do that by eliminating features. You do it by relating how each product feature benefits the buyer. There is no ecommerce niche where a fluffy paragraph of imagined benefits will outsell a well-crafted paragraph full of relatable features and their associated benefits. It doesn’t matter if you’re selling cuddly soft toys or cell phones. Features are equally as important as benefits. While you should, of course, give product specifics, what people really want to know is how the product helps them, solves their problems, and what they can achieve with the product. The key is to combine the key features and the benefits each provide. Understanding the difference between a feature and a benefit is the first step.
  • A feature is a fact or characteristic of your product.
    • Resolution, size, weight, connectivity options, ports, included software, and similar all count as features.
  • A benefit tells the reader how the product or a feature of that product benefits them.
    • How it solves a pain point or problem, how it improves efficiency, saves time, money, and so on.
Let’s take a look at a bed. People don’t want to buy a bed — they want to get a good night’s sleep. However, they need to know the features and how they are of benefit to make an informed purchase. Features only: “This bed has a four-drawer divan base and a memory foam mattress.” Benefits only: “Enjoy a wonderful night’s sleep on this mattress and divan base in your uncluttered bedroom.” Feature/benefit structure: “Keep your bedroom organized and uncluttered with this four-drawer divan base. The memory foam mattress cradles your body, eliminating painful pressure points and ensuring your body remains in the proper alignment, giving you a restful, comfortable night’s sleep.” Therefore, when determining product description length, make sure you leave enough room to accommodate a proper feature/benefit structure.


Keep it concise. Avoid cliches, jargon, and fluff at all costs. People don’t want waffle – they are busy and their time is limited, so get to the point. Don’t use 20 words when 11 will do. And don’t be vague and ambiguous. Employ clarity in your product descriptions. Consumers don’t want a bamboozling intellectual challenge, they just want to know if the product they’re looking at meets their needs. Avoid fluffy, salesy, promotional language. It’s a major turnoff. The modern consumer is smart and savvy and won’t be hoodwinked by exaggerated claims and over-promises. Be honest. And don’t try to sell to your reader – inform them.

In Summary

Product description word count depends on many factors, and it’s part art, part science — too little content, and you send potential customers away to find the information elsewhere, too much, and you lose potential customers who are intimidated by big walls of waffly text. Make it easy for your visitors to make a purchasing decision. Concern yourself with the clarity and quality of your content and how it improves the user experience. And use the experts here at eZdia as your ecommerce content solution provider – we’re an outstanding resource for seo analysis and improvement, and product copy.
Microblogging: how to effectively use Tumblr & other social microblogs for SEO, PR, content testing and beyond!

Microblogging: how to effectively use Tumblr & other social microblogs for SEO, PR, content testing and beyond!

Microblogging-how-to-effectively-use-Tumblr-other-social-microblogsBusinesses of all types are using microblogging to promote their brand, products and services. From the owner of a local corner bakery to the independent clothing retailer located downtown, companies can now quickly, easily and affordably spread the word about their offerings.

Marketing blogs can be found on popular microblogging platforms like Tumblr, Google+, Heello, Instagram, Tout, Vine and so many others. These marketing tools allow companies to operate simple, yet effective, business blogs that get the brand’s message out to a large target audience in a few important sentences, images or quick (6 seconds!) videos.