Synergies between lead generation and marketing automation

Authored by Soumya Pattanayak, MarTech Head at BlinkX by JM Financial 

While 91% of marketers consider lead generation the most critical marketing goal, 61% state that it is the most difficult task. This is because business growth is driven by lead quality, i.e., the potential to convert rather than the mere number of leads. This is where marketing automation has proven its worth, with 77% of marketers saying that it significantly improves conversion rates. This explains why the marketing automation industry is forecasted to grow at a CAGR of 12.8% from 2022 to 2027, to reach a value of $9.5 billion. Here’s a deep dive into how marketing automation can enhance lead generation.

What is Marketing Automation for Lead Generation?

Did you know from awareness to discovery, a B2C customer’s journey can be as short as 5 minutes? Marketing and lead generation best practices accelerate the movement of customers through the sales funnel. Marketing automation encompasses all aspects of brand representation, customer interaction, relationship building, behaviour analysis, and product recommendation to help accelerate this journey.

Impact of Marketing Automation on the Sales Cycle

Marketers experience a 14.5% improvement in sales productivity by automating marketing. The technique leverages machine learning-based analytics to assess customer needs and AI-powered recommendations to engage prospective and existing customers with the right content at the right time. It eliminates delays and complexities from the pathways that lead the customer to what they need.

The data-centric process optimises resource utilisation by pushing customers faster through the sales funnel. Some of its top benefits are:

• Reducing customer interaction overheads and manual workload.
• Improving lead scoring by identifying and nurturing leads with implicit buy signals.
• Expediting responses to customer queries, elevating the pre-purchase experience.
• Aligning the content to each stage of the customer’s journey – attracting, creating awareness, piquing interest, conversion, and advocacy.
• Personalising experiences across the stages of the customer’s lifecycle using data-derived insights.

Smart recommendation engines use the power of AI and ML to translate the benefits of data analytics-based predictions and generative recommendations. This can be effective in not just attracting potential traders to a platform but keeping existing users engaged and active. Intelligent hyper-personalized nudges can stimulate activity while risk-tolerance-based strategy suggestions ensure a great trading experience.

Marketing Automation Strategies to Maximise Results

The following strategies have proven instrumental in achieving the KPIs of fintech:

Automation for Lead Segmentation

Lead segmentation facilitates grouping traders based on their trading preferences, such as instruments, timings, and risk tolerance.

Personalised Email Marketing

Email marketing is considered the best way to engage clients for the long term and build loyalty. Personalised emails lead to higher open rates and ensure targeted learning to keep traders engaged.

Social Media Automation

Automating timed social media posts boosts engagement levels for different types of clients. For instance, a 9-5 worker will engage with evening content that concisely delivers value. However, a full-time trader would prefer detailed videos, especially during non-trading hours. This technique helps streamline lead-qualification workflows to distinguish high-scoring ones and target engagement better.

Optimising Landing Pages

Marketing automation maintains an engagement database. It offers the most welcoming first experience, based on customer preferences derived from ML-powered analytics.

Enhance Lead Generation Resources

Automation helps businesses expand across the ever-evolving digital space and emerging communication channels without additional overheads.

Analytics-Driven Insights for Improvement

The best part of data-driven marketing automation is that analytics-based engines self-assess their performance and refine the approach to better cater to diverse market segments.

AI/ML-based marketing automation strategically makes innovation and inspiration client-centric. It paves the way for ClienTech, a methodology of tailoring technology and its applications to user requirements, improving customer experiences throughout their journey with a brand.

DISCLAIMER: The views expressed are solely of the author and Adgully.com does not necessarily subscribe to it.