Especially companies dealing with B2B-customers nowadays use marketing automation to aid oftentimes small marketing teams with the demands of big sales units. But how does marketing automation work for B2C-companies?
Which specific functions do marketing automation systems have to offer B2C clients, to help support their marketing activities?
Many basic functions of a marketing automation systems are similar for either B2B or B2C companies. However, there’s a few differentiating requirements that a marketing automation system for B2C needs to fullfil. To identify and understand these, we first have to look at the basic differences between B2C and B2B business models and their individual marketing strategies.
Whereas B2B deals with relationships between two companies, B2C is about relationships between a company and private customers. This provides the fundamental difference when it comes to the requirements for a marketing automation system.
B2C customers purchase differently
B2C customers usually decide more impulsive and emotional than companies do. Additionally, so called „Buying Centers“ within companies make sure that the decision is based on the opinions of multiple decision makers whereas B2C customers usually decide on their own.
Since B2B-decisions also quite often involve bigger investment sums, the decision process involves more steps and takes longer, there are multiple decision phases involved that need to be addressed.
B2B lives by creating long lasting relationships between the vendor and the customer. That’s why most B2B customers are more loyal than B2C customers.
Customer loyalty programs are therefore a preferred means for B2C customers to create a bond with the company and motivate additional purchases. This includes campaigns like coupons, loyalty programs, competitions, etc.
A marketing automation system used for B2C customers therefore needs to be able to support these strategies by making it possible to send out individualized discount codes, etc.
Another favorite marketing strategy for B2C customers is cross- and up-selling, meaning that customers get product recommendations based on their recent purchases. For this, companies need recommendation engines to generate suitable recommendations based on the purchase history.
Social media for B2B and B2C Customers
B2C customers often use social media platforms which gives B2C-marketing an important platform to reach (new) customers. This includes platforms like Facebook, Twitter, Instagram, Pinterest, etc. For B2B-companies, platforms like LinkedIn and Xing provide a better way to connect.
Customers use these platforms increasingly to inform themselves about products and companies and exchange experiences . The monitoring and analysis of this behavior are highly complex and necessitate a marketing automation-connection with social media platforms that needs to be more in-depth than for B2B companies.
The 360° view on the customer
Most B2B companies already use a CRM system that connects different platforms and channels. However, many B2C companies have not more than an online shop and therefore need a proper connection to an eCommerce system to gain insight into the customers‘ behavior and provide communication and information throughout the whole customer journey.
B2B customers and B2C customers have different journeys, different spending habits and different relationships with companies. That means that their customer value and the variables that determine the value differ vastly. B2B marketing usually uses lead management whereas B2C prefers the customer lifecycle model. The marketing automation system therefore needs to adjust to these different methods to determine customer value.
What does marketing automation offer for B2C?
Marketing automation offers a lot for B2C business, by automating marketing processes, individualizing communication and reducing complex marketing processes.
Considering the points I’ve already mentioned, a marketing automation software for B2C companies needs to be able to:
create customer loyalty programs with individual codes, links and offers
use recommendation engines (e.g. using customer analytics for product recommendations)
provide social media monitoring and management
connect with eCommerce-systems and shops
include lifecycle models and customer value calculations
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