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This article is by Featured Blogger Abhi Yadav from his blog Forbes. Republished with the author’s permission.
The high cost of relying on rewards, rebates and discounts to buy customer loyalty has increased. Instead of buying based on loyalty programs, consumers are often making purchases based upon the brand’s relevancy as it compares to their needs at the time of purchase. According to the “Living Business” study by Accenture
As the CEO of a customer analytics platform company, I believe it’s important to understand how many transactions are being processed, but knowing this information won’t help you improve the relationship you have with your customer. In order to fix this, you need to understand why a customer buys, and why they chose to have a relationship with your brand in the first place. In order to deepen your relationships and relevance with customers, you need to move beyond transaction data and use customer data that will help you meet consumer expectations of an authentic brand relationship.
Why is relevance important? The same Accenture report referenced data from its 2018 survey of more than 24,000 global consumers and found that 68% of consumers who perceive a company as relevant are more likely to recommend that company to friends and family. It was also found that 61% of customers switch brands based on relevance, and 29% of customers said they would stop doing business with companies they don’t perceive as relevant.
The Last Of The Five Ps: Personalization
Most marketers are familiar with the traditional four Ps (subscription required): product, price, place and promotion. However, there are another five Ps to consider: purpose, pride, partnership, protection and personalization. The last of which is a critical component to relevancy.
Personalization helps the consumer feel like the business they are buying from is specifically relevant to them. The concept of personalization has evolved from simply including a person’s first name in an email to giving customers the relevance they need. It allows companies to offer targeted experiences where the buyer’s journey matches their interests. This also allows businesses to make better use of their marketing spend.
Improving Relevance With Continuous Customer Analytics
Using continuous customer analytics can allow you to improve your customer focus. It can help you deliver the right message to the right person at the right time, improving your brand’s relevance. To take it a step further, with advancements made in technology, and using automated customer analytics, we are at a stage where you can now predict possible online behavior of your audience.
Don’t make the mistake of sticking to a rigid mindset of being product-focused. To be relevant, you need to be customer-focused instead. Use consumer sentiment as a cornerstone for your content marketing strategy. So, instead of typical ad hoc business intelligence (BI) reports for Monday morning meetings, make the transition to tracking customer intelligence (CI) dynamic reporting.
Using continuous customer analytics will help you determine what your strategy should be and allow you to do numerous A/B testing at scale. By focusing on individualized content and predicting user behavior, you can improve your relevance and customer focus.
Tips For Focusing On Relevancy
1. Optimize the customer journey. Prioritize tracking the customer journey with AI and machine learning across all customer touch points.
2. Use analysis to improve content. Analyzing your data can help you discover new relevant keywords and select blog post topics. This will improve your content creation process making it more relevant to your core audience. As messaging becoming more accurate, it should improve sales effectiveness and lead generation while reducing sales cycles.
3. Use ID resolution. ID resolution allows you to match customer data across devices and siloed systems. This ensures all customer records are tied to a single record using deterministic and probabilistic matching.
4. Leverage all your customer data for a more personalized experience. Leveraging all customer data continuously is more useful than using limited data in marketing cloud/campaign tools. This allows for an individualized offer and personalized content to be recommended at the right time.
5. Use customer life cycle automation to find out what is causing customer churn and reduce it. By doing so, you can gain insights from the acquisition through reactivation. Using risk prediction and intervention models, you can calculate how different levels of intervention might affect the customer lifetime value and reduce churn.
Becoming More Relevant To Your Customer
Make sure to include personalization so that all of your customers’ user experiences are tailored to their needs. It’s no longer enough to have customer loyalty programs; you must remain relevant to your customers to continue a fruitful relationship.