IT professionals and decision makers are becoming increasingly aware that implementing technology without a clear cut need does not contribute to customer retention. New forms of technology may enable IT professionals and decision makers to help firms with treating customers more personally based on their unique behaviors, and for a surprisingly low cost and relatively low effort.

Over the last few years we’ve been seeing buzz words such as “big data” and “business intelligence” (BI) being flung around everywhere. Many agree that getting all these insights about customer behavior and tendencies can be game changers for their business, and some companies are known for practicing it. Amazon and eBay know what products could interest me based on how I behave in their respective stores. Insurance companies and financial institutions use big data to define risk, and actuarial calculations. But many other verticals still find behavioral analysis, big data, and BI, somewhat confusing.

The good news is that now we’re starting to see more BI and data platforms that are relatively inexpensive, promise rapid deployment, and yield a direct connection to revenues and KPIs. These platforms take the practice of data analysis and the desired corresponding action, from abstract to pragmatic. Their low footprint, and result driven-design is perfect for the medium and small enterprise. And since this work is applied to existing, consent-providing customers, the recent Canadian Anti-Spam Legislation (CASL) restrictions do not apply.

What companies are using

Companies like the gifting service startup Giftagram, use tools such as Marketo, MixPanelEloqua and others to establish a nurturing platform that allows for defining customer segments based on common behaviors, for example, all customers that haven’t made an order in the last 30 days, or who have browsed a specific product category recently but haven’t finished the transaction. By using these tools you can create as many segments as you’d like, matching various criteria relevant to your business. These segments let you collect statistical information about your customers, and would also form the basis for the logic of your customer relationship nurturing activities.

Once you understand your relevant customer segments, you create “campaigns” based on these segments. A campaign is a set of rules consisting of your desired reactions to specific customer behavior as defined by the segment. Some basic campaigns that you might include based on your customer behavior would be:

  • Communication to potential customers who haven’t been on your site before
  • Customers that haven’t used your app or site in a while. You could initiate incentives such as discounts or gifts for customers to come back and generate transactions.
  • Customers that are exhibiting social behavior (e.g. spend time on social networks), where you can communicate a request to share info about your service in return for promo codes.

Once you understand the comfort levels of any specific customer segment, you will be able to work within their acceptable boundaries, and proactively increase their engagement with your products or services.

Improve your business strategy

Throughout the campaign lifecycle you can utilize multi-variant communications around specific events and monitor your customers’ reactions to a message delivered using slightly different language to numerous smaller subsections. The statistical analysis you gather based on customer reaction to your different approaches, will let you gauge and perfect the communication for the entire segment, creating fine-tuned touch points with the customer that feel very personal and relatable.

Creating campaigns involves understanding critical business data points and how they correlate with instances of your digital presence. In other words, understanding the business drivers is not enough, you also need to a thorough understanding of your website, customer portal, or app code, and how they all integrate with your back-office, ERP, and CRM. You need to isolate specific events and actions in the code, and analyze information flow across your systems as it corresponds with customer behaviors, and their related segments. You will also need to program some of the corresponding campaign activities back into the systems, e.g. front-facing user interfaces, or financial/ERP promo related calculations. Needless to say that this initial customer nurturing framework creation requires both technical, and business resources (marketing, sales, operations), and as such, leads to a fantastic cross-departmental collaboration providing real business value.

Campaigns are fast-acting in delivering results

Once created, the campaigns immediately start addressing your existing client base, generating communications, activities, and follow-ups while keeping track of their success rate in fulfilling KPIs, and generating revenues. So if you communicate promo codes to one of your segments, you will see how many customers came back to your site or app as a direct result of the campaign. You can even see how much additional revenue the campaign generated, and get a better understanding for how to incentivize your customer base. Moreover, the campaigns are perpetual and self-sufficient. Depending on how you set them, campaigns can continue and operate routinely, analyzing new customers’ behaviors and applying actions accordingly in an ongoing fashion.

If you understand which behaviors and outcomes are currently important to your business, set up relevant campaigns and update them once in a while with tweaks. But after that, you’re done building. Now you can collect business data in real-time or through predefined reports, outline corresponding actions, and decide on whether the data necessitates new business goals, or is sufficient for now. This ‘build-once, then hands-off’ approach leads to a relatively low-cost entry point into the customer nurturing practice, utilizing data analysis and business intelligence, and yielding very favorable results.

I’m excited about the practical uses of data analysis and business intelligence within the customer nurturing practice. What do you think? I’d love to hear from you and continue the conversation.

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