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Modern B2B Supplier Approach and Customer Experience

In the previous article What Do B2B Buyers Expect from Their Suppliers, we have explained the change that happened, and is still happening to B2B buyers, and how B2C approach influences them. Now, we want to focus on the behavior of modern B2B buyers, and their experience, which impacts the way their suppliers approach the process of B2B selling.

Business Intelligence upgraded into Predictive Analytics gives us high quality inputs, just in time when we need them, so we can make fast, yet smart decisions about improving the experience of our B2B buyers. It answers some key questions raised by every company in B2B business:

What kind of buying experience the modern B2B buyers expect from their suppliers?
Why is it necessary to optimize your B2B portal for all devices, especially mobile?

Here are the essentials every online marketer should understand...

What Do B2B Buyers Expect from Their Suppliers

Changes have happened in the way B2B buyers look at the process of purchasing goods from their suppliers. And most of these changes are not easy to see, even though some of them are not small, until you dig deeper into the behavior and expectations of modern B2B buyers. But, in order to explain these changes, let's ask ourselves one important question. What is B2B, and B2C, and how they differ?

B2B buyers purchasing products online

Direct Benefits of Predictive Analytics for eCommerce

There is a huge number of goals to achieve in eCommerce, more or less important, and the same number of ways to measure the results and success of this approach: increasing sales, increasing profits, increasing customer base, increasing the number of customer purchases, maximizing sales per customer, maximizing sales per purchase, growing future business, being more visible, advancing brand reputation and recognition, minimizing customer abandonment etc. After setting these goals and employing advanced models in Predictive Analytics, successful Online Retailers will experience direct benefits from:

Benefits of Predictive Analytics

How to Apply Predictive Analytics in eCommerce?

Predictive Analytics uses BI data for forecasting and modeling. It uses Predictive Analysis to predict future patterns, and support managers in making better business decisions. With this advanced decision support system, managers evaluate the probability of future events, based on events from the past. Predictive Analytics incorporates advanced algorithms (statistical, data mining, machine learning) capable of revealing patterns beyond the power of traditional BI (Business Intelligence) tools.

Applied to eCommerce, this means collecting relevant information and employing the powerful algorithms of Predictive Analytics to help Sales Managers target the right customers, ones who are likely to respond positively, with products or services they are likely to enjoy, and at the time they are likely to buy.

Predictive Analytics Advanced Dashboard for eCommerce

Why Use Predictive Analytics in eCommerce?

Retail world changes rapidly and dramatically, influenced by two overriding factors. First one is technology. The second one, strongly affected by the first is consumer behavior. Only a few decades ago, being a retailer was much simpler and easier. The store represented one and the only place for creating consumer experience. With the rise of Information Technology, personal computers, internet, and finally mobile devices (smart phones and tablets), retail businesses faced multiple challenges in their struggle to attract and retain customers.

Predictive Analytics - view on a mobile device

1. Be aware that consumer behavior and habits are changing

2. Focus on consumers and their behavior

3. Focus on technology...

The Imperative of Website Optimization for Mobile Devices

There are several reasons why all website owners should decide to optimize their online asset for mobile devices. Even though we tried, we couldn't find any good reason for the opposite. This is the time when mobile devices are overtaking the internet space. More and more people use them, and many of them have more than one device. Mobile phones are used on the go, in public transportation, during sports activities, at work, at home, everywhere.

website optimization for mobile devices

How To Calculate ROI for Mobile Stores?

It is well known that in today’s overcrowded global market, the biggest challenge is to sell your product or service. Many people are capable of producing fine products, but not all of them are good at selling them successfully. And that is the key to a successful business. The evolution of sales started centuries ago, but real diversification of sales channels exploded during the 20th century. From traditional retail sales, over direct sales, B2C and B2B sales, telesales, marketers have been struggling to find the best way to acquire customers for their products or services. Internet brought new opportunities and dramatic changes for the world of sales. That’s how we got eCommerce. But what is the next step that perfectly follows and undergoes the habits of modern humans from 21st century? Yes, you’re right. It is Mobile Commerce, which in fact is, Online Commerce optimized for mobile devices.

eCommerce Technology Distribution in Canada

Free Online Test Tools to Check Your Website Mobile Readiness

You most likely know that Google is now using mobile-friendliness as a significant ranking factor. Websites that are not properly optimized for mobile devices will achieve lower rankings in mobile search results; and this is no small matter, given that mobile internet usage has now overtaken desktop usage.

If you’re still unsure to whether or not your site is mobile-friendly, here are 3 online tests you can use to determine the mobile-friendliness of your site.

Data Mining for Predictive Social Network Analysis

Given this enormous volume of social media data, analysts have come to recognize Twitter as a virtual treasure trove of information for data mining, social network analysis, and information for sensing public opinion trends and groundswells of support for (or opposition to) various political and social initiatives. Twitter Trend Topics in particular are becoming increasingly recognized as a valuable proxy for measuring public opinion.

This article describes the techniques author employed for a proof-of-concept that effectively analyzed Twitter Trend Topics to predict, as a sample test case, regional voting patterns in the 2014 Brazilian presidential election.

AUTHOR: Elder Santos