Бесплатный фрагмент - Direct Marketing Automation Guide for Beginners

INTRODUCTION

In today’s business world, marketing plays a key role in the success of any organization. Marketing is a set of activities aimed at market research, determining the needs and preferences of consumers, and developing and promoting goods and services that satisfy these needs. The goal of marketing is to create strong relationships with customers, increase sales and strengthen the company’s position in the market.

At the same time, marketing professionals can be roughly divided into several key areas: customer acquisition, retention and return.

Each marketing area has its own set of tools and methods. One such method is Direct Marketing — communicating with the customer through channels such as Email, SMS, mobile push notifications, phone calls and so on, directly.

Most times it’s expected that the customer has already shared their contact information: registered a personal account, subscribed to a newsletter, installed an app or became a member of a loyalty program. When you have a client’s contact, the main task is to retain it and “convert” the contact into an order or similar target action. And after that — into the next order. And so on.

This book dives into the use of direct marketing and associated strategies to transform website visitors into leads, convert those leads into customers, and ultimately boost revenue. It draws on insights from three hundred B2C companies along with my own extensive experience — over ten years in marketing automation with a specialization in customer retention.

I have tried to put the book together in such a way that once you understand a minimal amount of marketing automation theory and methodology, you can take the cases mentioned and apply them to your eCommerce business.

The book covers the following topics: the basics of direct marketing, key metrics and basics of direct marketing targeting, principles of marketing automation for online and eCommerce, and examples of marketing automation software. Each topic is provided with plenty of examples.

I hope this book will be a useful guide for students, entrepreneurs, marketers, and anyone interested in direct marketing who wants to develop their professional skills in this field.

ABOUT THE AUTHOR

Filipp Volnov is a renowned CRM expert in Russia and the CIS, with more than 10 years experience and knowledge in marketing automation. As one of the leading authorities in the field, he has been lecturing on CRM at Yandex Practicum, Russia’s largest online eLearning platform, sharing his insights and expertise with a wide audience.

In addition to his educational endeavors, Mr. Volnov served for 7 years as a leading customer success manager at Mindbox, the #1 cloud Marketing Automation platform in the ex-USSR region.

Mindbox is currently ranked among the top 5 B2B SaaS companies in the region, further solidifying author’s position as an authority in the industry. Over the past decade, he has managed a team of 10, generating an average annual revenue of more than $2 million. Throughout his career, Mr. Volnov has published over 30 success stories of various brands, showcasing the power of marketing automation in driving growth and efficiency.

Mr. Volnov was also responsible for managing marketing communications at Mindbox. He actively participates in conferences, exhibitions, and webinars, as well as oversees publicity in magazines and newspapers. His dedication to promoting marketing automation and sharing his wealth of experience has made a significant impact on the industry, and this book serves as a testament to his commitment to helping businesses unlock the potential of marketing automation.

In this book, the author unveils a unique marketing automation strategy developed over years of personal experience, which has consistently demonstrated a revenue increase of 10–25% from DTC marketing across many different industries. The strategy is divided into seven key customer journeys, each illustrated as a map and supplemented with real-life case studies and A/B testing ideas. Drawing from a wealth of expertise, the author provides valuable insights into the world of marketing automation, guiding readers through the process of implementing and optimizing these crucial chains for maximum impact and revenue growth.

THE BASICS OF DIRECT MARKETING

Key terminology

Before we delve into examples and study the experience of companies in the field of direct marketing and its automation, we want to understand the basic terms and concepts.

— Direct marketing — communication with the client “directly” through Email, SMS, phone call, chatbots, letters

— Target Audience — A group of potential customers to whom marketing efforts are directed.

— Segmentation is the process of dividing a market into segments with homogeneous needs and preferences.

— Personalization — tailoring marketing materials to a specific customer or group of customers.

— Conversion — the percentage of consumers who take a targeted action (e.g., purchase) out of the total number of consumers who received a marketing message.

— ROI (Return on Investment) is an indicator of the effectiveness of marketing investments, calculated as the ratio of profit received to the cost of a marketing campaign.

— LTV (Lifetime Value) is a metric that estimates the total amount of money a customer brings to a company over the entire time of cooperation. LTV allows you to determine the value of a customer to the business and is used to determine the effectiveness of marketing strategies, manage budgets and make decisions about long-term investments. LTV calculation involves analyzing the average revenue from a customer, frequency of purchases and customer retention period.

— A/B Testing — A method of comparing two or more versions of marketing materials to determine which is most effective.

— Direct Marketing Channels — Communication media used to deliver marketing materials such as email, SMS, phone calls, mailings and others.

— CRM (Customer Relationship Management) is a customer relationship management system designed to store, process and analyze customer data and automate marketing campaigns.

— Customer Retention is the strategy and activities of companies to retain existing customers and encourage them to buy or use services again.

OBJECTIVES OF DIRECT MARKETING

The tasks of direct marketing are different for every company, but I would highlight the following that I have encountered in practice most often:

— Attracting new customers and increasing the customer base: if we consider the website as one of the communication channels, then popups for collecting subscriptions are a tool for attracting new customers.

— Increase sales through customer retention: direct marketing allows you to maintain relationships with current customers and ensure their loyalty.

— Getting feedback: direct interaction with customers provides an opportunity to collect feedback and suggestions that can be used to improve the product or service.

— Exploring customer needs and preferences: analyzing data collected through direct marketing campaigns to identify factors influencing customer choices and identify opportunities for growth.

— Motivate repeat purchases: direct marketing can be used to remind customers of offers and promotions, encouraging them to make additional purchases.

In the end, direct marketing is about keeping the customer with the brand for as long as possible, maintaining interest through personalized offers, recommendations, unique discounts and exclusive content.

For example, the clothing brand 12 STOREEZ makes private sales for subscribers, and the clothing brand ALL WE NEED regularly sends a collection of unique looks and stylist tips to the e-mail.

WHAT METRICS ARE USED IN DIRECT MARKETING

Companies measure the effectiveness of direct marketing through a number of metrics, most of which are related, well, to money. With a few exceptions, of course: some companies can’t always track the connection “down to the money’: for example, when sales data “lives separately’ in other data silo from emails (more often than not, that can be fixed!), or sales are made in a location not related to the brand in any way.

For example, a FMCG manufacturer Kimberly Clark sends email campaigns to a base of subscribers who then buy Huggies diapers at Costco or Amazon. In this case, it is possible to trace the connection between campaigns and sales only by finding a correlation in bursts of marketing activity and the background of sales.

In most cases, the businesses I’ve had the opportunity to work with have used the following metrics:

— Share of direct channel revenue in total year revenue

— Order conversion compared to the control group

— Retention rate, or customer retention rate

— Absolute revenue of the channel for the period

— Average check per customer for the period

— Increase in active customer base

If a business hasn’t tracked marketing metrics before, I recommend choosing at least one metric to start with that is closer and clearer to the business and is easy to implement. Let’s break down each metric in more detail.

Share of direct channel revenue in total revenue

Formula

Revenue share from Direct Channels = (Direct channels revenue / Total Revenue) x 100%

Benefit

Shows how much money, relative to other channels, direct customer interaction channels — SMS, email, mobile, web and messengers — bring to the business.

For example, store 12 STOREEZ set a goal to increase the share of revenue from direct communications. The point is that customers began to read newsletters less often and it was necessary to bring back the interaction that was conducted through five channels: email, mobile push, SMS, web push, OSMI Cards push notifications. The store audited the mailings, began working to improve the effectiveness of each with AB tests, and conducted a survey of inactive subscribers. The results: the share of revenue from direct communications grew to 30.43%. That is, almost a third of revenue came from customers who were already in the base and didn’t need to spend budget to attract them. If a business has only an email channel, consider the share of the email channel in total revenue.

Risks in tracking the metric

The share of revenue from direct channels grows, but the total revenue does not. This is likely to happen if, for example, direct channels “ate” the revenue of other channels. That is, the revenue of direct channels has grown not because they are efficient, but because the revenue from other channels has been redistributed to direct channels.

To know exactly what caused the metric to rise, I suggest tracking the share of direct channel revenue in conjunction with total revenue and using a test with a control group. In marketing, control groups are used to measure the impact of a specific campaign or customer journey. Specifically, control groups are the customers you are targeting with a particular campaign who will not receive that campaign.

Conversion to order

Formula

Order conversion rate = (Total orders number / Total number of visits) x 100%

Benefit

Shows how marketing affects the number of orders from a particular channel.

Online supermarket Arbuz.kz implemented personalization and marketing automation. In order to track how it affects sales, it measured the conversion rate from going from an email to an order, and compared email channel performance YoY.

Result: conversion to order from email increased by 23%. So, marketing automation has improved conversion rates. The next step is to calculate how much money it brings in.

Risks in tracking the metric

If you don’t compare it with a control group, there is a risk of drawing the wrong conclusions. A fairly common situation is when a customer comes from context ads to a website, creates an account, receives a welcome email flow, follows the link and makes a purchase. Analytics tools show that the customer made a purchase attributed to the welcome email because it is the last significant communication channel.

Revenue from such a purchase will be at the share of the email channel. If a customer has left a mail on the website, most likely they are interested in buying something. We need to find out whether the welcome letter plays a decisive role and to which channel it is fairer to attribute the purchase — to mailings or contextual advertising. This can only be done by conducting a test with a control group. As part of the test, some customers will receive a welcome letter after registration, while others will not. If the background of sales in these groups is different, it means that the welcome letter really influences the decision to buy. In this case, it is logical to attribute the purchase to the welcome email flow.

Retention rate, or customer retention rate

Formula

Retention Rate = ((Number of customers at the end of the period — Number of new customers) / Number of customers at the beginning of the period) x 100%

Benefit

Shows whether the business is succeeding in retaining customers through communications.

For example, grocery store Galamart wanted to increase online store sales, including selling more to loyalty program members. To do this, it launched an omnichannel loyalty program, personalized mailings, and tracked RR as an indicator that the goal had been achieved. The result: RR growth, 12% customer return.

Risks in tracking the metric

Inability to see how retention rate growth affects revenue. There may be a situation when RR is growing, but revenue is not. It is possible that the company receives less revenue from new customers. To see this, I suggest comparing the revenue from new customers and those who bought before.

Setting an inappropriate target. Goals for this metric can vary greatly from business to business. For example, for an online furniture store and a pet supply store: furniture is not bought as often as pet food, so the share of repeat purchases will be lower. It is important to set a goal, taking into account the specifics of the industry and historical data.

Absolute revenue of the channel for the period

Formula

Total channel revenue = Total revenue from product sales within the period

Benefit

Shows how much money has been earned through a particular channel.

For example, the online electronics and home appliances store “OGO!”, with which I have been working for several years, set the task of increasing revenue. To do this, I launched several types of automated mailings: standard and specific emails, and web beepers. The result: the revenue of mailings from all channels of direct communication is about $100,000 a month.

Risks in tracking the metric

There is no understanding of how much the company actually earns through marketing. This can be the case if the analytics do not capture the exact number of orders. Orders are duplicated, not displayed in real time, and returns may not be counted at all.

In order to properly track real revenue, you need internal analytics from order placement to redemption — it should include all orders, without duplicates and including returns.

I suggest tracking the absolute revenue of one channel against other channels, just like the revenue share of an email channel, for example.

Average check per customer for the period

Formula

Average Order Value = Total revenue / Total orders number

Benefit

Shows how the amount of the average check is changing — whether customers are spending more.

A large pharmacy chain had several objectives: to reduce the cost of launching promotions, increase the average check and increase the reach of its loyalty program. To do this, the company personalized promotions for program members. The result: the average check of loyalty program participants is 61% higher than that of non-participants. This means that the terms of the loyalty program are attractive to customers.

Risks in tracking the metric

The average check is increasing, but the total revenue is not. A possible reason for this is that the number of purchases has decreased. For example, the month before last the revenue amounted to 20 million roubles. The average check was 2,000 rubles, because there were 10,000 purchases. And last month’s revenue was 15 million with an average check of 2,200 rubles. In order to see how the average check affects the growth of total revenue, I advise you to track these metrics in conjunction with each other.

Share of active customer base

Formula