Take a multi-channel approach to data analysis

[sourovk291]

You need to gather customer insights across different channels to get a more holistic view of your audience and create a solid digital marketing plan. The three main ones are website, social media, and email.

Website
With website data analytics, you dig deeper into user data such as overall traffic, unique page views, content interactions, and more. For example, you can gather detailed user insights from a heatmap or A/B test.

Let’s say you want to attract more leads into your sales funnel, but they’re not coming through. You may not even realize it, but glaring CTA design mistakes are hurting your conversions. You can implement A/B testing and see which CTAs are most powerful at attracting leads.

Tools for website data analysis: Google Analytics 4 (aka GA4) - for traffic and engagement, AB Tasty - for A/B testing, Mouseflow - for heatmaps.

Social networks
Social media data analysis will give you detailed insights into how customers interact with your posts and ads.

This way, you will be able to understand how to engage your audience more effectively and leverage social media for sales, based on the following factors:

I like

Comments

Views

Shared

Impressions

Sentiment (positive, negative or neutral)

For example

The Leya AI team actively uses Meta ads (formerly Facebook ads). However, ad performance is different psychiatrist email database every time. Check out this video ad.


Multi-channel approach - Meta Ads by Leya AI
Source: Facebook.com

And now, an image ad that got far fewer likes, comments and shares.


Customer data analytics -Meta Ads - Leya AI
Tools for social media data analysis: Buffer, Hootsuite, Social Insider

Email
Email data analysis focuses on the following characteristics of emails:

Delivery capacity

Opening rate

Click-through rate

Reading time

Conversion rate

Unsubscribe rate, etc.

Once you translate this data into actionable insights, you'll be able to write stronger emails that delight and convert every customer.

Email data analysis tools: HubSpot, Klaviyo or SmartLead.ai

Implement customer segmentation
Imagine you have accumulated customer data in a big pile.

And now what?

Your next step would be customer segmentation .

By segmenting customers into distinct groups or categories based on their shared characteristics, brands see more productive marketing results.

Need numbers?

There you have it. After segmenting their B2B audience, Scorpion Healthcare increased conversions by 56% on LinkedIn. What’s more, customer data segmentation has huge potential for email marketing . Open rates for segmented emails are typically 14.31% higher than for non-segmented campaigns.

First, you need to divide customers into groups, and then create individual segmented profiles based on characteristic traits such as:

Needs: requirements, concerns, pain points

Behavior: purchasing habits and behavioral patterns

Demographics: gender, ethnicity, age, education, occupation.

Geography: state, region, climate, language, cultural preferences

Psychographics: interests, vital values, moral code, temperament, character type.

Business data (for B2B): industry, business type, company size, sales volume.

Technology data (for B2B): devices, applications, innovations.

For example:

Kinsta , a WordPress hosting provider, segments potential customers by firmographic factors such as company size, number of employees/site, and others, and diversifies pricing options. Additionally, potential customers can discuss with the sales team a custom plan that fits their specific requirements (needs-based segmentation).