objective

The goal of this project was create an effective digital marketing strategy for a bank based on the results of a machine learning clustering algorithm that we developed. The objective was to segment its customers into meaningful clusters, thereby allowing the bank to tailor its sales and marketing efforts for each cluster.

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Previously, the bank had a one-size-fits-all marketing strategy that did not maximize the future value gained from its customers. However, our AI-driven digital marketing approach allowed the bank to lower acquisition costs, increase customer lifetime value, increase brand awareness and loyalty, and develop effective sales funnels.

digital marketing strategy & implementation

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Audit

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As a successful ROI-driven digital marketing strategy begins with an audit of current capabilities and marketing campaigns, we first conducted a thorough audit of the bank’s existing strategy, goals, systems & procedures, and marketing campaigns. We identified the bank’s SEO (Search Engine Optimization) ranking, lead magnets, tripwires, social media marketing campaigns and paid advertisements, PPC (Pay-Per-Click) Google AdWords, and so forth. After the audit, we recognized that the bank’s marketing strategy, goals, and implementation methods did not align with its overall business objectives and desired brand perception.

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Current Strategy Pitfalls​

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More specifically, the bank previously followed a one-size-fits-all approach. In other words, it did not distinguish between its different groups of customers but instead assumed that all of its customers were the same in that they valued similar qualities and had similar needs. This one-size-fits-all-approach is suboptimal and leaves money on the table, as the bank actually had multiple different customer segments with differing needs, value drivers, demographic characteristics, and behavioral tendencies.

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Need for Customer Segmentation

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Therefore, we developed a digital marketing strategy that accounted for the 8 different customer clusters that we identified from the machine learning algorithms developed. As such, we created 8 different sales funnels to address the needs of each cluster individually. This was essential to increase the ROI of every marketing dollar spent. Instead of wasting money on the wrong channels, targeting the wrong people, and mismatching content with the wrong audience, our approach identified the needs and characteristics of each distinct cluster.

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For instance, we identified the best marketing channels (and combinations of channels) to reach each cluster, understood the types of products that each cluster demanded based on its demographic and behavioral characteristics, and designed content/messaging that would dramatically increase the likelihood of resonating with each cluster.

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Organic Growth​

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For each sales funnel, we prioritized organic traffic at the beginning of the implementation stage. We did this in a variety of ways: by boosting the bank’s SEO ranking, by creating unpaid and targeted social media posts, by optimizing the user experience on the bank’s website, by implementing content marketing, and so forth.

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Hyper Growth Phase​

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Once we created brand awareness and trust through organic methods, we shifted our focus onto PPC ads, targeted paid social media ads, and retargeting strategies to further drive traffic and boost awareness. These are only some of the lead generation techniques that we used, which drastically improved the bank’s digital presence and customer user experience.

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Optimization using Data Analytics​

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During the implementation phase, we also optimized the bank’s marketing campaign through data analysis. We analyzed the content that drove the highest amount of traffic, understood the reasons why they worked, and improved future content to best resonate with the bank’s customer segments.  

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Aligned with Overall Business Objective

It is also important to note that we created the digital marketing strategy in a way that aligned the bank’s overarching brand goals and business objectives with its marketing campaign strategy and implementation methods.

results

The AI-driven digital marketing strategy, which was highly targeted and deliberate, successfully generated a high ROI (Return on Investment). By understanding the needs and behavior of the different customer segments, we lowered the bank’s acquisition costs, generated more and better leads, created higher conversion rates, improved the bank’s social media presence, increased the CLV (Customer Lifetime Value) of its current members, shortened its current sales cycle, and improved its customer retention rates.