Monitoring each marketing channel is critical to determining what worked (and what didn’t) to drive conversions.
Was it the first point of contact, the last one, or something in between that helped in converting the prospect into a customer?
For instance, in B2B marketing, your ideal customer may begin a buying journey from a Google ad and then interact at different points -
- An industry webinar
- Targeted LinkedIn ads
- A series of educational emails
- Detailed product demo
Often, three key attribution models are used:
- First-Touch Attribution
This model credits a potential customer's first interaction with your business for leading to a conversion.
Example: If a prospect discovers your brand through a LinkedIn ad and eventually signs a contract, then full credit is assigned to the LinkedIn ad. It ignores other interactions that happened afterward, like attending a webinar or talking to a sales rep. - Last-Touch Attribution
Opposite to FTA, this model attributes the success of the conversion to the last interaction before the sale or lead conversion.
Example: When a potential client attends a webinar and signs up for your service, LTA credits the webinar as the sole influencer. It does not credit the last touch even if they first discovered your brand through Google Ads. - Multi-Touch Attribution (MTA)
MTA recognizes that multiple touchpoints contribute to a lead's conversion. It attempts to distribute credit across several interactions.
Example: Consider the above two examples where a prospect discovers your brand through Google Ads, attends a webinar, and signs up. However, it is challenging to accurately determine how much credit each interaction deserves, which is complex and subjective.
So, what will you assign weightage to?
This is where you’d give weightage to each attribute, based on how it impacted the prospect's decision to turn into a customer.
Attribution Feels Flawed: Here’s Why!
Attribution models, while valuable, are flawed because they oversimplify the customer journey and fail to capture the complexity of multiple interactions across various channels - online and offline.
This leads to skewed or incomplete insights.
Such a limitation means you need more than these models for comprehensive marketing decisions.
Key reasons why attribution models, including MTA, will be dead!
- Data Fragmentation and Silos
When weighing each touchpoint across different platforms, the challenge is to create a unified view of the marketing funnel.
Measuring ROMI from social media ads, email marketing campaigns, and other activities is tough because customer relationship management (CRM) systems might use different data formats and metrics.
Even if you are successful in fragmentation, it will leave gaps in data. This makes it difficult to accurately track and attribute customer interactions across the journey. - Ignoring External Influences
No attribution models consider external factors (like market trends, competitor actions, economic shifts, and socio-political events) influencing the customer's decision-making process.
Suppose you're marketing a cybersecurity solution. News of a sudden rise in cyberattacks may cause a surge in interest and sales. However, traditional attribution models may incorrectly credit this spike solely to your recent marketing campaigns. - Data Deprecation
As a marketing leader, you must also adhere to data privacy and regulation. This means exercising caution when collecting and using the data, particularly affecting deterministic MTA (Which means the conversions are attributed to specific marketing channels or campaigns).
This challenge, known as data deprecation, can be broken down into key points:- Privacy Regulations and Consent Management
Regulations like GDPR and CCPA demand transparency and trust in customer relationships. You must honestly communicate how you will use the data, which can affect the quantity and quality of data voluntarily shared by users.
- Cookie Deprecation
Major browsers are phasing out third-party cookies. This reduces the ability to track user behavior across the web. You can use MTA, but this reduces its effectiveness in accurately attributing sales or conversions across different websites and digital touchpoints.
- Privacy Regulations and Consent Management
What Can You Do to Fix the Issues with MTA?
There are hurdles in relying on touch-based attribution, including MTA.
However, progressive companies are pursuing more holistic strategies to address these limitations. The key is to ensure a seamless integration that captures the full spectrum of customer interactions.
So, we have some strategies you can adopt to effectively manage your marketing and sales efforts.
The outcome?
A more cohesive and efficient approach to understanding and influencing the customer journey.
- Bridge Online and Offline Data
You will consider all the digital touchpoints, but what about the offline ones?
What about the lead form data you capture in B2B networking events, conferences, trade shows, etc.?
Capture data from these events and feed it into your CRM system to assign weightage to offline events in the sales funnel.
Here's what to do:- Event Lead Capture Tools: Leverage digital lead capture tools like Cvent LeadCapture, iCapture, Bizzabo, etc., in offline events for integrating lead data directly with your CRM. Consider using QR codes on business cards or brochures, which can link to digital forms for easy data capture.
- Direct Sales Feedback: Train the sales team to promptly input detailed notes and outcomes of their interactions into the CRM system.
- Ask Prospects from Where They Hear about Your Brand: Inquire prospects at offline events, whether they've previously encountered your brand online or offline. This approach helps precise lead attribution to sharpen your understanding of customer pathways, essential for refining marketing strategies.
Next, logging these responses in the CRM significantly sharpens the synergy between online and offline marketing efforts.
- Use Unique Identifiers
The MTA method may be useful if you can track individual campaigns and initiatives. - Coupon Codes and Special Offers (in B2B partnerships):Implement unique coupon codes or special offers/discounts specific to each partner to track your sales through partnership channels.
- Using UTMs:Use unique identifiers like UTM to track content downloads and direct outreach efforts, like email campaigns. This helps track which pieces of content and emails are driving engagement and contributing to lead generation.
This provides a deeper analysis and understanding of how each element contributes to the marketing strategy.
Some ways to implement it:
- Integrating Qualitative Insights
Blend the qualitative insights to understand the deeper, often non-quantifiable aspects of customer behavior and preferences. This approach goes beyond traditional metrics and looks at the subjective experiences and opinions of the customers.
Here's how to do it: - Collect and Analyze Qualitative Data
Customer Interviews: Conduct in-depth interviews with customers to understand their experiences and feelings about your brand and its touchpoints. While they have left the sales funnel, interviewing them offers insights into which touchpoint worked.
Social Media Monitoring: Analyze comments, reviews, and discussions on social media platforms to gauge customer sentiment and gather feedback. Hootsuite's. sentiment analysis tool can be a good starter for understanding the tone and sentiment of customer responses.
Surveys with Open-Ended Questions: For those yet to convert, send open-ended questions in surveys (over emails), allowing them to express their thoughts independently. Focus on the stories customers tell about their experiences and how they describe their journey with your brand. - Integrating Insights with Quantitative Data
Data Triangulation: Combine qualitative insights with quantitative data (like click-through and conversion rates) to get a complete picture of the customer journey.
You'd need advanced tools like SPSS Text Analytics by IBM, NVivo, SAS Text Miner, etc., to analyze text responses and relate them to numerical data patterns.
Customer Journey Mapping: Incorporate qualitative insights into customer journey maps to add depth and context to each touchpoint. Assign the qualitative insights to the appropriate touchpoints on the journey map.
For example, include customer emotions, thoughts, or direct quotes representing their experience at each stage. Next, use visual elements to represent these qualitative insights on the journey map. This could include icons, emoticons, or color coding to indicate different emotions or experiences.- Actionable Strategies
Personalized Marketing:Now that you have insights, leverage them to tailor marketing messages and campaigns to different customer segments based on their preferences and experiences.
Improving Customer Experience: Maintain Good CRM Hygiene - Actionable Strategies
Effective CRM hygiene is crucial in surmounting the hurdles presented by touch-based attribution. It ensures data integrity and reliability, which is the cornerstone of accurate attribution analysis.
What do you need to do?
Clean, update, and verify CRM data regularly to gain a clearer and more consistent understanding of customer interactions.
Some tactics to improve CRM hygiene that fuels data-backed decision-making.
- Data Integration Across the Sales Funnel Integrate data across the sales funnel stages - from initial customer awareness and engagement to post-purchase behavior.
- ML algorithms like linear regression, classification, clustering, etc.
- NLP algorithms like sentiment analysis and text classification
- Convolutional Neural Networks(CNNs) for image recognition
- Recurrent Neural Networks (RNNs) and Long Short-Term Memory Networks (LSTMs) for time-series analysis, such as predicting customer churn over time.
- Anomaly detection algorithms to identify unusual patterns that do not conform to expected behavior.
- Anomaly Detection to Identify Process Leaks in CRM
Identify irregularities or deviations in data that indicate process inefficiencies or errors. For instance, if there's a sudden, unexplained drop in customer engagement metrics, this could signal a problem in data entry or a glitch in tracking interactions.
Example: Your marketing campaign may show higher conversion rates despite high engagement. Anomaly detection can reveal that the leads are not correctly logged in the CRM, leading to a false representation of campaign effectiveness.
Do - - Set Up Automated Alerts: Ensure your CRM tools are set to automatically alert you of unusual data patterns. These could include significant changes in customer engagement or lead conversion rates.
- Conduct Data Audits: Conduct periodic audits of your CRM data to check for consistency and accuracy. Search outliers in data entries that don't align with known patterns or expectations.
- Offer Employee Training: Provide team training for efficient data entry and understanding the common pitfalls that can lead to data anomalies.
- Cross-check with External Benchmarks: Compare your data with industry benchmarks to spot any discrepancies that might suggest internal process leaks. Look for online research and market surveys when setting a benchmark.
- Funnel Breakdowns in CRM for Enhanced Attribution Analysis
- Defining Clear Funnel Stages: Establish and maintain clear definitions for each stage of your sales funnel in the CRM to accurately track the customer journey.
- Monitoring Drop-off Points: Analyze where potential customers drop out of the funnel. Look for patterns or commonalities among these leads to identify underlying causes.
- Aligning Marketing and Sales: Aligning marketing and sales teams on funnel stages requires a shared strategy and communication platform. Both teams have access to the same customer data and insights that feed the cross-departmental meetings for sharing performance metrics.
- A/B Testing: Experiment with different strategies at stages with high drop-off rates to see what works best in advancing leads through the funnel.
- Correctly setting up Google ads conversion packing
When dealing with incorrect conversion tracking in Google Ads, it's essential to reassess and recalibrate your setup.- Review Conversion Actions: Ensure conversions you track in Google Ads are aligned with your key business objectives. It requires tracking actions like form submissions, purchases, or phone calls.
- Check Tag Implementation: Verify that your Google Ads conversion tags are correctly implemented on your website. Tools like Google Tag Manager and Google Tag Assistant
- Align with CRM Data: Cross-reference Google Ads conversion data with the corresponding entries in your CRM. Here, discrepancies indicate issues in tracking or data entry.
- Test and Validate: Test conversion tracking by creating controlled scenarios like submitting a test form. Then, check if these actions are recorded precisely as conversions in both Google Ads and your CRM to verify that the tracking system functions correctly across platforms.
- Ensure Sales Reps Keep CRM Updated
Sales reps may forget to enter or update sales-qualified leads (SQL). This makes CRM data incomplete and potentially misleading, affecting the accuracy of sales forecasts and marketing strategies.
What can sales personnel do?- Daily Updates: They can update CRM data at the end of each day to ensure all interactions and progress are recorded.
- Mobile CRM Access: Use mobile CRM applications to update information on the go, especially after meetings or calls when details are afresh.
- Integrate with Email and Calendar: Sync CRM with email and calendar apps to automatically log meetings, calls, and emails with clients, reducing manual data entry.
- Set Reminders: Use CRM reminders or task lists to prompt regular data updates, ensuring no interaction or progress point is missed.
- Customer Segmentation
AI tools help segment potential customers based on their digital behavior patterns, industry, company size, and other relevant demographics. This allows for more targeted and relevant marketing approaches.
Tools like Salesforce Einstein offer predictive lead scoring that assigns high scores to leads based on their conversion likelihood. This allows prioritizing of sales and marketing efforts towards the most promising prospects. - Use Predictive Analytics: AI-driven predictive analytics can identify patterns in customer behavior and preferences. This helps segment customers more accurately according to their potential needs and value.
- Incorporate Multiple Data Sources: Combine data from various sources like social media, website interactions, and purchase history for a comprehensive view of each customer.
- Dynamic Segmentation: Update customer segments regularly as AI tools continue to learn from new data, ensuring segments remain relevant and effective.
- Personalized Marketing Campaigns: Use AI-segmented data to tailor marketing campaigns, ensuring messages resonate more effectively with each targeted group.
Leverage;
This often requires using Python (with libraries like scikit-learn, TensorFlow, and PyTorch), R, or platforms like IBM Watson, Google AI, or Microsoft Azure AI.
Analyze large datasets (CRM, website analytics, social media, etc.) to clean, process, and unify data from various sources like CRM systems, website analytics, social media, etc.
You'll segment the customer journey into distinct stages to pinpoint where leads are lost, or conversions falter.
Such segmentation helps identify specific touchpoints that may be underperforming or overlooked.
Chances are, your funnel shows a significant drop-off in customer progression between the 'initial meeting' (2. Discovery) and the making of an offer (3. Evaluation). This could indicate issues like inadequate follow-up processes or lack of engaging content to move leads to the next stage.
Optimizing the funnel requires -
Key tactics for effective customer segmentation:
Want to take this to the next level?
Use advanced analytics that goes beyond typical Marketing Touch Attribution (MTA). It requires an understanding of the sales funnel and prospective customers’ behavior.
That’s where Revlitix comes in.
How Revlitix Can Help?
Revlitix offers a marketing mix model that simplifies understanding and simulates marketing investments' effect. Features like Reports and Playbook optimize your tactics and the delivery medium.
Revlitix Reports for Funnel Overview
A 100% customizable setup with Revlitix allows tracking KPIs by importance. You get funnel breakdown reports to replace traditional methods like Google Sheets.
Get the real-time AI signals on funnel leaks Reports identify and highlight issues in the marketing funnel in real-time.
This includes pinpointing campaign performance issues or areas of process ineffectiveness, allowing you to take proactive measures to optimize the funnel.
Here, you can check conversions at each touchpoint and assign the weightage that turns insights into actions.
This is where workflow automation comes in.
Workflow Automation and Rule Building: Revlitix automates manual audits and process checks to create custom rules that track and validate hypotheses.
You will be notified of any anomalies so you can explore them in detail.
Pipeline Forecasting with Revlitix
As discussed earlier, you’d need predictive modeling to forecast assigning weightage to each attribution source.
With Revlitix Pipeline, you can identify potential issues before they impact campaign performance.
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We also provide recommendations to auto-fix campaign and tool errors, optimizing campaigns effectively based on AI-detected performance leaks.
Adhering to Data Privacy and Compliance
Revlitix Security offers a variety of features to help businesses with their marketing analytics, including pipelines, reports, alerts, and playbooks.
We take data security seriously and have implemented measures to protect customer data, such as encryption and access controls. Also, we are committed to transparency and have published the privacy policy and terms of service.
A quick overview of how we ensure data privacy and security:
- We secure customer data using TLS for data in transit and encrypt data at rest within the application. This ensures strong authentication and authorization controls for data access.
- Data at rest is encrypted with AES-256 or better, using symmetric keys that are regularly changed and stored in a secure key store.
- Data in transit is protected using HTTPS and SHA-256 with RSA encryption, additional encryption, and authentication at network layers outside AWS or AWS-controlled boundaries. Also, the data within Revlitix's Virtual Private Cloud data centers may be transferred unencrypted.
- We also use a multitenancy approach where customer data is tagged with unique tokens and separated logically. It needs API keys and secrets for access (where web UI needs authenticating usernames and passwords), ensuring data isolation between different clients.
Conclusion
Sticking to traditional attribution methods may fall short. So, adopt the best of both worlds to get a comprehensive view of the customer journey and adapt to the rapid changes in consumer behavior.
Ideally, advanced analytics and AI-powered solutions like Revlitix can be a game-changer here. You can now integrate data across the entire sales funnel, analyze customer behavior, and predict trends to allocate resources for maximum ROMI.
Ready to take the next step? Get more from your existing data to outsmart the competition.
Sign up for a free trial or connect with team Revlitix for more details.
