Campaign to Closure

Understanding the overall customer base

R Systems’ C2C solution is geared towards organizational growth by increasing the effectiveness of their omni-channel marketing efforts, generating more sales, tracking compliance and creating customer loyalties by aiding customer service across various stages of the buyer journey.

Campaign to Closure (C2C) is a proprietary solution by R Systems, that offers a wide range of Analytics capabilities that are compatible with both big data & legacy, on-premise & cloud infrastructure.

C2C Solution Approach:

Popularly known as the S-T-P approach, this helps organizations plan their marketing objectives across different channels, thus ensuring products & services are positioned in a way that resonates with the selected target market/segment.

The key here is to understand the customer-base or target audience of any products/services that an organization is looking to market/sell. This is done by understanding the overall customer-base, defining the right customers for the right products, and making informed decisions by deriving actionable insights.

Our Services Include

The first step involves understanding the overall customer base via Customer Segmentation. This is a process of dividing a broad customer-base/business market, normally consisting of existing & potential customers, into sub-groups based on some type of shared characteristics.

Based on the type of business, the two broad categories of segmentation -

B2B Segmentation

B2C Segmentation

Now that we looked at how Campaign to Closure helps segment the customer base, the next step is to identify which of these segments to target for marketing – the use case that is popularly known as Lead Generation or LeadGen in short. There are various ways to target a population to generate leads – can be based on age, occupation, gender etc.

But, the reality is that there’s no “one-size fits all” model for LeadGen, or for any one of the other C2C use cases for that matter. And just like the other use cases, C2C provides multiple models/options in LeadGen too. When we prepare to deploy, we analyze the best fit model for our clients.

The next step after determining who to contact, is How to contact them! Enter, Channel Analytics – C2C’s next key use case!

Top-3 Common Problems

Business Preferring a Specific channel – But, with multi-channel marketing, we lose the control of funneling users to one specific medium.
More Moving Parts to Manage – Wherein, with so many channels and so little time, it can feel overwhelming trying to harness the multitude of mediums.
Increased Time & Expense – Because, there’s so much more to manage with multi-channel marketing, businesses may probably have to devote more time.

B2B Segmentation

The target market for any B2B product or service is not one homogeneous mass. Rather, it can be divided into several distinct groups based on who they are, how they behave, what they want or what they think. In the Campaign to Closure solution, we have 3 main approaches to B2B segmentation:

A priori segmentation (Firmographic): We use a classification scheme based on publicly available characteristics — such as industry and company size — to create distinct groups of customers within a market. However, we have observed that companies in the same industry and of the same size may have very different needs.
Needs-based segmentation: We use differentiated and validated drivers that customers express for a specific product or service being offered. These needs are discovered and verified through primary market research.
Value-based segmentation: Here, we differentiate customers by their economic value - grouping customers with the same value level into individual segments that can be distinctly targeted.

B2C Segmentation

Similarly, we have four basic segmentation approaches for B2C Segmentation -

Demographic segmentation: This is the B2C version of firmographics. Demographic segmentation divides customers based on aspects such as age, gender, education, occupation, income, marital status etc.
Geographic segmentation: Here, we group customers based on geographic location. It allows companies to focus the products and services offered to different segments based on where they are located.
Behavioral segmentation: In behavioral segmentation, we divide customers based on attributes such as brand loyalty, awareness, knowledge, social media interaction and purchasing patterns. Although it is difficult to implement, it allows for precisely targeted marketing messages.
Psychographic segmentation: In this approach, we group customers based on personality, lifestyle, values and social class. Similar to behavioral segmentation, this can be difficult to implement, but the payoff in precise marketing is significant.

C2C’s Problem Mitigation Tactics

De-Silo Channels: Coordinate cross-promotional efforts with integrated marketing in which different mediums complement each other.
Set Control Groups: Test the effectiveness of your multichannel marketing efforts by setting control groups that do not receive the multichannel promotion. This will help you better measure your campaigns’ effectiveness.
Create Multiple Touch Points: Touch points can include social media, surveys, email newsletters, mail-in items, etc.
Know Your Audience: What channels will work best for your business? Where does your key audience spend most of their time? This information should greatly influence your multichannel marketing approach.

Channel analytics based on actual preference

In this option C2C incorporates customer channel preferences through which they would want to be contacted. These channels typically include phone call, text message, email, direct mail etc. Essentially this is a rule based model to define a set of channels of each customer.

Channel analytics based on surveys

As the name suggests, in this approach, we typically design and conduct a market research surveys in which a uniform mix of candidates are chosen to take the survey. The advantage with this method is that we can control the representation of certain sections of the population by oversampling or under sampling techniques.

However, this approach heavily relies on assumptions around the absence of any kind of bias in the survey questions and sample. Also, since this data is self-reported, there might not be a concrete method to verify the actual truth.

Channel analytics based on similarity

This is the flagship solution offered by C2C. In this method, we identify similar customers and determine the most appropriate channel based on this similarity. We use multiple techniques like Euclidean distance, Cosine and Jaccard similarity coefficient to measure the similarity between customers. Then we build a collaborative filtering based recommendation engine to essentially recommend the best channels for marketing. This helps offer personalized experience to customers.