How we help with
customer Analytics & activation
CUSTOMER ANALYTICS IS MORE VALUABLE THAN EVER
Traditional thinking in customer analytics is broken. Privacy regulation (e.g. GDPR), internal compliance policies, walled gardens (e.g. Apple), and disparate data hinder measurability, limiting effective customer acquisition cost control and CRM-growth from first-party data use cases.
In the customer analytics of tomorrow, we navigate this situation by modelling and analysing first-party data to provide the answers that most brands need now more than ever:
How do we lower our rising customer acquisition costs?
Which customers are most profitable to us, and is their lifetime value optimal?
If our churn rate is worsening, what’s the most profitable way to stop this?
How relevant are our products and prices in the market?
Traditional thinking in customer analytics is broken and managing the end-to-end customer journey becomes increasingly important.
We approach this challenge via three enablers. The first enabler is identifying your best customers and finding the next growth opportunity. The second is adopting ML/AI for efficiency and enhanced capabilities, and the third is collaborating and automating in marketing operations.
Customer Journey Management
Increasing customer lifetime will have a direct impact on the value of the customer base and business.
Our solution predicts which customers that will potentially leave your company and why. This gives you the opportunity to initiate a proactive retention strategy with several activities.
Predictify Consulting will continuously report who, when and why your customers are potential churners.
Customer Retention & Churn Prediction
Directing ressources towards leads with high potential value is critical for sales channels to grow the customer base.
Our solution predicts which consumers that are more likely to become a customer and at what value level for the company. Having a priority guide will assist your sales and CRM dept. in allocating their ressources towards leads with the largest potential.
Predictify will continuously report who, why and how much value your leads are representing.
Customer Lead Scoring & Conversion Optimisation
Who should be targeted in your win-back activities and through which channels?
Lost customers represent a potential value that must be activated quickly; in most companies within six months. Because your company know their past preferences and purchase history we can help you estimate likelihood of win-back success.
Predictify Consulting will continuously report who, why and how much value your win-back leads are worth.
Customer Win-back & Re-activation
Customer Journey Analytics: Where the next, best profitable customers are activated
Data owned by your company holds many critical answers if analysed in depth with advanced modelling methods and tools.
Since 2000, we have been reducing customer acquisition costs and elevating customer lifetime profitability across the end-to-end customer journey with best-in-class Customer Analytics and ROI. Always safe and compliant.
The business opportunities arise from unifying and sharing first-party and third-party data leveraged from data clean rooms and identity-related technologies. This ecosystem economy emerges from data-sharing developments, helping brands establish savvy (but secure and privacy-compliant) inter-industry partnerships that amplify their customer journey intelligence.
Ever signed up for an internet provider or booked a painter on your realtor’s site before moving to your new home? That’s one example of an easy-to-imagine ecosystem economy.
Moving from imagination to amazing business outcomes takes cutting-edge practices to save you time and money. These practices use AI/ML and advanced analytics as an extended arm to help you get the most out of your marketing and buying channels. And with our unique Third-Party Data Activation service we can make your brand even more relevant to the customers unlike any other.
In short:
Businesses turn to Customer Journey Analytics to create a consistent and relevant buyer’s journey, that outperforms competitors, and boost customer lifetime revenue.
Customer Journey Analytics helps you connect all the dots in today’s fragmented customer journey and unlock data that is siloed within your organisation, enabling you to predict the next best customers. This leads to a better understanding of your customers, allowing you to tailor your services to their preferences and expectations, ultimately improving their experience with your company.
We engage in three stages:
How to approach Customer Journey Management
What is Customer Journey Management
Customer Journey Management is the practice of monitoring, analysing, and optimising every step a customer takes when interacting with a brand, from initial awareness to post-purchase engagement. The goal is to create a seamless, consistent, and personalised experience for customers across all touchpoints, including marketing, sales, customer service, and product use
We work across three enablers to prioritise and optimise marketing disciplines throughout the customer journey:
Customer Journey Management Model
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Know your best customers and how to grow:
Who are our most profitable customers?
Which marketing disciplines should we activate to better grow this base?
What roadmap is the best to deliver on our business objectives and KPIs?
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Know how to adopt ML/AI for efficiency & stronger capabilities:
What target state for data science and ML/AI capabilities should we aspire for?
How can we implement data science modeling for better ROI?
What capability roadmap is the best to deliver on our business objectives and KPIs?
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Know where to collaborate and automate in marketing operations:
How can we integrate data-driven practices into our daily operational processes?
What steps can we take to enhance cross-team collaboration using advanced analytics?
To which extend can we automate data flows and reduce manual turn-around times and flaws in the future?
IMPLEMENTATION ENABLERS
CUSTOMER JOURNEY ACTIVATION
How to get started with customer analytics in Predictify Consulting
Customer analytics starts with the collection and handling of various types of data. This is to gain insights into the customer’s behaviour, preferences, and interactions with your business in the context of your business model and go-to-market situation.
Nearly all our projects begin with incomplete or inconsistent commercial data, but with our proven approach, we turn all relevant, disparate data into actionable data.
On top of this, Predictify has years of experience in building analytical models and effective data flows – all we need is access to the relevant data, no matter the shape or form.
Get in touch for tailored sales and marketing solutions
Curious about how we can help improve your sales and marketing performance?
Feel free to reach out – we’ll respond promptly.
customer analytics projects
Customer analytics involves collecting and analysing varius types of customer data to gain insights into their behavior, preferences, and interactions with a business. The key interests and benefits of customer analytics are depending on companys challenges, strategy and business model.
At Predictify we have years of experience helping companies improve customer engagement whether focus is on intake, ARPU or retention. Here are some of the key areas where we have helped our partners:
Improved Customer Understanding
Segmentation: Identify and group customers based on similar characteristics, allowing more engaged and targeted marketing .
Enhanced Customer Experience
Personalisation: Offers and communications to individual customer preferences, increasing satisfaction and loyalty.
Predictive Modelling: Anticipate customer needs and behaviour to proactively address issues or offer relevant recommendations.
Effective Marketing Campaigns
Targeted Marketing: Identify the most receptive customer segments for specific products or services, improving the efficiency of marketing efforts.
ROI Measurement: Evaluate the performance of marketing campaigns and channels to allocate resources effectively.
Customer Retention
Churn Prediction: Identify customers at risk of leaving, allowing for proactive retention strategies.
Loyalty Programs: Design and optimize loyalty programs based on customer behavior and preferences.
Optimised Product Development
Feature Prioritisation: Understand which product features are most valued by customers, guiding development priorities.
Innovation: Identify new product or service opportunities based on customer needs and feedback.
Operational Efficiency
Supply Chain Optimization: Forecast demand more accurately, reducing excess inventory and improving supply chain efficiency.
Customer Service Effectiveness: Respond faster to customer data to enhance the quality and efficiency of support processes.
“Where there is data smoke,
there is business fire”
- Thomas Redman, aka “the Data Doc”