{"id":532,"date":"2017-05-03T12:34:22","date_gmt":"2017-05-03T09:34:22","guid":{"rendered":"https:\/\/rees46.com\/blog-en\/?p=532"},"modified":"2017-05-10T21:27:06","modified_gmt":"2017-05-10T18:27:06","slug":"progressive-personalization-in-online-retail","status":"publish","type":"post","link":"https:\/\/rees46.com\/blog-en\/2017\/05\/03\/progressive-personalization-in-online-retail\/","title":{"rendered":"+24% Sales: What Is Progressive Personalization in Online Retail?"},"content":{"rendered":"

\"\"<\/p>\n

First, a little about personalized product recommendations. Those, who already know what we are talking about, can skip to the next point.<\/span><\/i><\/p>\n

So, what does it look like? Imagine, somebody visits your online store and notices on the main page products of interest to that person. Your visitor may have read marketing or tech reviews on the newest MacBook model and now sees different configurations of that model in your catalog. The same happens if somebody browsed through the category \u201cRunning Shoes\u201d in your store \u2014 this visitor is shown popular models of the running shoes you sell.<\/span><\/p>\n

<\/p>\n

Your main page is not the only place where this story happens. A visitor can see product recommendations on category pages, product detail pages, shopping cart page, even your 404 page.<\/span><\/p>\n

What we just described is called product personalization, and it is one of the pillars of modern eCommerce.<\/span><\/p><\/blockquote>\n

Product personalization is not only about your website. Everybody has seen email newsletters featuring a block of recommended products at least once. The same goes for display ads showing us the items we left in the cart in some online store or lightning-fast web push notifications with a link to a personally tailored selection of recommended products.<\/span><\/p>\n

Long story short, product personalization has been for a while and is remaining a crucial part of marketing strategy in online retail. You\u2019re very unlikely to find a store that is successful without any kind of personalization, except maybe a mono-product store or a small local one.<\/span><\/p>\n

What you may yet not know is that the regular, Big Data-based, personalization may quite often turn it from cure into a trap for an online retailer.<\/span><\/p>\n

Big Data <\/span>\u2014 <\/b>a Well-hidden Trap<\/span><\/h2>\n

\"\"<\/p>\n

A Big Data-based personalization is way too far from the perfection many wants you to believe in. Here are some critical issues you\u2019ve probably never recognized before.<\/span><\/p>\n

Illogical Recommendation Logic<\/span><\/h3>\n

Statistical data is what drives a Big Data-based personalization. It means that if enough customers have bought this crib or that laser printer along with that coffee maker, these two will be shown in the recommendation to the coffee maker. Just take a look at this example:<\/span><\/p>\n

\"\"<\/span><\/p>\n

There is no viable logic in this case. The recommendations don\u2019t match the primary product, but Big Data is Big Data, and you cannot argue with statistics.<\/span><\/p>\n

Universal Does Not Mean Precise<\/span><\/h3>\n

Big Data is not the most precise tech in online retail. Earlier, we mentioned the running shoes example. What do we have to add to it? Yes, the visitor will see the most popular models. Yes, those will be running shoes. Is this enough for the recommendation to catch the visitor and for purchase to happen? No.<\/span><\/p>\n

The final purchase decision in each retail segment \u2014 Apparel & Accessories, Construction & Repair, Auto Products, Pet Products, Consumer Electronics or Home Appliances, Cosmetics & Beauty \u2014 is affected by a very specific set factors varying from segment to segment.<\/span><\/p>\n

For instance, an Apparel & Accessories store needs to recommend items by gender. The items must also correspond in size. Nobody needs another pair of favorite running shoes if they\u2019re two sizes smaller or an XXL hoodie when your size is XS.<\/span><\/p>\n

It can be illustrated by the following example: while a visitor of Forever 21 chose and added to the cart an XS hoodie, he can still see recommended items in the wrong size.<\/span><\/i><\/p>\n

\"\"<\/p>\n

As you\u2019ve already guessed, these are Big Data-based recommendations:<\/span><\/p>\n

\"\"<\/p>\n

Some items are in the wrong size, for instance, this white muscle tee is available only in XL:<\/span><\/p>\n

\"\"<\/p>\n

Big Data chooses to skip this fact. Somebody may overlook this while others will see a critical issue. What\u2019s certain is that there are retail segments where such attitude to personalization can harm the customer and, therefore, your business.<\/span><\/p>\n

Big Data Can Do Harm <\/span><\/h3>\n

Take a good example \u2014 FMCG (Fast-Moving Consumer Goods). Some products in this category are strong allergens to a lot of people while posing no threat to others. Also, there are customers with illness treatments prescribing a strict diet and another portion of your audience with no such limitations.<\/span><\/p>\n

In an ideal marketing world, product recommendations momentarily recognize everybody and adapt to the new requirements on the go. Big Data is far from ideal. As a result, store recommends a customer with personal allergies products containing the allergen.<\/span><\/p>\n

A situation where a diabetic deliberately buys a milk chocolate bar full of sugar or a lactose-intolerant person \u2014 a regular yogurt is hardly possible. However, these useless to the customer products will be taking up space in the recommendation block wasting your money, while other relevant products are skipped. No relevance to the buyer equals no sales.<\/span><\/p>\n

What Is Progressive Personalization for Niche? <\/span><\/h2>\n

Progressive Personalization is a new technology that progressively and constantly adapts recommendations to each new visitor, each time he changes his behavior. The ultimate goal is to keep the recommendations highly relevant excluding non-fitting products from the block.<\/span><\/p>\n

The Progressive Personalization technology has been developed by REES46 Technologies and serves as the base of \u00a0<\/span>REES46 Marketing Suite<\/span><\/a> \u2014 a set of marketing automation & personalization tools for online retail.<\/span><\/p><\/blockquote>\n

Taking into account each retail segment has a different set of key factors affecting the purchase decision, such as pet type and breed for pet products or skin type and current condition for cosmetics, REES46 has Niche Solutions for each specific retail segment.<\/span><\/p>\n

Let\u2019s focus on few and see the principles this tech works by, and give our interested readers links to more detailed descriptions.<\/p>\n

Progressive Personalization in Pet Products Niche<\/span><\/h3>\n

A cat owner is not to be recommended food formulas for dogs or fish. An Alsatian owner is not to be recommended products fitting small dog breeds. Now that you have those two basic examples, let\u2019s see the whole list of key parameters for this segment:<\/span><\/p>\n