5 Data-Driven Techniques To Understand Your Customers

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Customer experience optimization can be an innovative way to get new customers. Importantly, it is the top method to promote and nurture customer loyalty. Generally, customer behavior data can really help in creating an optimization strategy. However, less than half of marketing executives use custom behavior data4. To compound the problems, company leaders ignore customer nurturing before and after the sale. Usually, the obstacle is a lack of deep understanding of the customer. Data collection and analysis is a critical part of modern marketing. There is no structural reason not to optimize the customer experience in a data-driven manner.

Having a complete and broad appreciation of your customers’ behavior, likes, and dislikes is a core-solution to achieving company goals to achieve business goals. 

It doesn’t matter what your company’s goals are:

  • Construct and optimize the customer experience?
  • Develop salient and appealing content?
  •  Increase sales numbers. 

No matter what the goals are, having a deep understanding of your customers’ individualized behavior is essential. These data will help you achieve your business goals, increase engagement and sales, and make your company a leader in its field.

Use Scientific Techniques To Engage Your Customers

All customer engagement data, good or bad, will yield good data. That insight will allow you to optimize the customer experience, which is indispensable for customer retention and revenue generation. Every channel, whether real-time messaging apps to email communication to phone conversations, will yield proprietary information. These data need to be used in customer service team discussions to analyze patterns and test strategies. Furthermore, your team discussion, customer engagement data, and deep customer conversations will help your individualized customer development program. To create an individualized client persona (i.e., a marketing technique tailored to a specific customer), you need to have your customer service team schedule regular calls to get a “deep-dive” perspective. Only a good mix of quantitative and qualitative data will optimize your onboarding process, improve customer satisfaction, and increase your sales. When collecting customer data and responses to surveys, keep these principles in mind:

  • Put Bias Aside: Cognitive bias is when we systematically create a subjective reality different from objective reality6. In other words, we ignore outside signals and facts and stick to our false opinions. When asking a customer or prospect for their opinion, don’t project yours. Do not influence your customer; you may get a negative opinion, which may be unpleasant but is actionable.
  • Be Direct: You will need actionable data. To get that data, ask questions that are not vague. For example, ask: “Has our security software protected you from attacks?”. Your data will be harder to interpret if you don’t obtain concrete and relevant answers to your inquiries.
  • Be Targeted: Your questionnaires need to be topic-specific and tackle one area of the customer journey at a time. This way, you will engage your customer, and you will obtain actionable insights.

Individualize Client Personas

Evoke positive emotions in your prospects and customers. The goal of your marketing should be to tap at desires and problems at the individual level. Using generic metrics (e.g., using broad demographic, location, and time data) will not help, and it will waste valuable resources. Instead, work with your analytics teams to obtain data on:

  •  Which customers use specific social media channels (e.g., LinkedIn or Facebook?). 
  • Where your customers come from and when. 
  • What search terms your prospects are using (e.g., which keywords).

You may find out that you need to create different customer personas to offer the same service to a variety of clients (e.g., a wellness product’s potential to decrease inflammation may be of interest to an older clientele, whereas its performance-boosting effects may be of interest to a younger clientele). Having personas that resonate emotionally with your clients is the best way to improve customer engagement and sales.

Integrate, Process, and Analyze

Every customer’s action and inaction offers valuable insight into behavior. Work with your marketing team to create regular analyses and tests on your customers’ and prospects’ activity. Data such as session time (i.e., time on page), bounce rate, and traffic source (i.e., paid ads vs. organic) are invaluable. Some tools can provide videos of users on your pages in real-time8. Behavioral data collected will help you interpret what your audience understands and likes and what they don’t. For example, you may want to adjust your website for a more mobile-friendly experience. In any case, processing and analyzing data regularly will improve the customer journey.

Predict The Future

Predictions are real and statistically significant. Historical behavioral data will show you which of your service or product features prospects find valuable and which ones they don’t. Pages visits direct content strategy. To stay ahead of the curve and maintain a competitive edge, future customer engagement plans are critical for growth. A forward-thinking mentality focuses customer experience teams on responding to stressful or challenging customer experiences dynamically. 

If you’re a small company, most simple analytics tools (e.g., Google Analytics3 and Google Data Studios5) are more than enough to see historical behavior data and anticipate future behavior. If you are a large company, predictive modeling software can use modern machine learning and other advanced predictive techniques to mine and process your data to identify patterns and trends that will guide decision making2,7

In either case, using data-driven techniques to identify your company’s trends and comparing them to market trends will give you insight into your position in the competitive space. Predicting the future is critical for product and service development and for reducing business risk. When you know exactly where you’ve been and where your stand, you can decide where to go.

Walk In Your Customer’s Shoes

To fully appreciate the details that attract a prospect and convert them into a paying client is to map the entire journey. Customer journey mapping is when a detailed, visual representation of the customer journey is created based on critical engagement points1. These points, minor or major, are recordable instances when a customer engages your service. These include, but are not limited to, downloading an app, following you on social media, buying a product, paying an invoice, and/or opening an email. The key is understanding, exploring, and analyzing what circumstances affected the decision of each engagement point. For example: 

  • What time of day and where did the client open an email? 
  • When and where did they download your app?

Concurrently, it’s important to understand failed engagement points, such as failure to use the app they downloaded. Using a data-driven customer journey, you can create milestones that you will use as metrics to re-engage your client (e.g., if they haven’t used your service in a month, it may be time to reach out to them). If you’re short on resources, an email marketing drip can be a great way to re-engage your customers.

Conclusion

Modern analytic techniques, behavioral recording methods, individualized customer engagement will yield increased sales and happier customers. Creating a bespoke experience for your clientele is easy and important for growth.

If you would like to learn more about analytic techniques, creating customer personas, and how to integrate your channels, please drop us a line or say hi on social media. Ad Science Lab always put our clients’ needs first. We succeed when you succeed.

  1. All You Need To Know About Customer Journey Mapping. (2015, January 16). Smashing Magazine. https://www.smashingmagazine.com/2015/01/all-about-customer-journey-mapping/
  2. Altair | Discover Continuously. Advance Infinitely – Only Forward. (2021). Https://Www.Altair.Com/. https://www.altair.com/
  3. Analytics. (2021). Google Marketing Platform. https://marketingplatform.google.com/about/analytics/
  4. Forbes Insights & Teradata. (2015). Teradata 2015 Global Data-Driven Marketing Survey: Progressing Toward True Individualization. Www.Forbes.Com. http://images.forbes.com/forbesinsights/StudyPDFs/Teradata-Data_Driven_Marketing-REPORT.pdf
  5. Google Data Studio Overview. (2021). Https://Datastudio.Google.Com/Overview. https://datastudio.google.com/overview
  6. Haselton MG, Nettle D, Andrews PW (2005). “The evolution of cognitive bias.”. In Buss DM (ed.). The Handbook of Evolutionary Psychology (PDF). Hoboken, NJ, US: John Wiley & Sons Inc. pp. 724–746.
  7. RapidMiner. (2020, December 4). RapidMiner | Best Data Science & Machine Learning Platform. https://rapidminer.com/
  8. Riese, G., D., Carr, S., & Hung, J. (2020). Stop guessing what your visitors want. Https://Www.Inspectlet.Com/. https://www.inspectlet.com/

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