There was a lot of talk about AI-driven marketing in 2017. But it’s no longer a new phenomenon. And as AI will be deeply integrated into every aspect of marketing going forward, the future belongs to marketers who can adapt to the technological advances – both to deliver instant gratification to consumers and to build more meaningful and deeper relationships with them.
As we continue into 2018, CMOs need to avoid simply embracing the next big thing, but instead rethink how they should manage and execute marketing to make it more personalized than algorithmic. It’s time to reassess your marketing.
Follow the steps I’ll outline below to reassess your marketing efforts and put them into the right perspective.
1. Capitalize on your data to help your customers make the best purchase decision
Data-driven marketing reigns now and always, simply because marketing that drives value is most effective. In this age of consumer-driven businesses, the main aim of marketing is to empower people to make the best purchasing choices and keep them engaged with your brand.
With access to a 360-degree view of customers, marketers can truly understand their customers. The customer intelligence gained from piecing together all customer data and interactions across channels offers a lot of actionable insights to deliver an ideal customer experience. And this is exactly how your favorite retailers are offering you a targeted experience with products and offers customized to your taste.
2. Use analytics to understand intent and predict
An Aberdeen study from just a couple of years ago found that only 19 percent of marketers track all of their marketing efforts to drive improvement via reporting. That may have improved since then, but it’s likely still way too low.
One of the biggest challenges CMOs face is the transformation of data into actionable insights. – Forbes
While many marketing leaders have data and analytics at their disposal, most aren’t leveraging them effectively. The goal of analytics is not just to measure ROI of the various marketing campaigns but also to know the impact of those promotions on each customer.
Analytical insights can further help marketers to sort multiple offers based on their previous purchases and behavioral attributes to make it a win-win scenario for both marketers and their customers.
Marketers are using analytics to create a dynamic customer experience in real time. The analytical marketers are driving big changes by harnessing data in real time for actionable insights.
3. Use predictive intelligence to segment your new (holiday) shoppers
The more strategically you segment, the better you can personalize. Don’t rely on old-school time-based segmentation to group all your newly acquired customers into the same segment. Instead, use predictive intelligence at the individual user level to focus more on those with year-round potential.
Leverage machine learning approaches for real-time prediction of the customer behavior and RFM modeling to create segments based on the recency, frequency and monetary value of the purchase.
Predictive intelligence can find patterns in your customer data to suggest:
- Customers with higher AOV (average order value).
- High LTV (customer lifetime value).
- Higher purchase probability.
Smart segmentation methodologies can help you use your marketing budget more effectively, and you can focus on the key segments instead of raining offers on all the newly acquired customers.
4. Take full advantage of embedded AI
AI has transformed the retail space forever, and it will continue to do so in future. From leveraging real-time data for personalization to attribution, automation, customer service and logistics, AI and machine learning will enable marketers to anticipate customer intent and enhance the customer journey by adding that missing human touch to every aspect of marketing.
5. More efficient integration and use of big data
A key challenge for CMOs is to seamlessly integrate customer data across channels.
The truth is, data integration may not sound as sexy as data-driven marketing, but that’s the source of all data. And making this happen falls not solely to tech but to all the departments across the enterprise. The solution is to implement a centralized platform for customer data collection across channels, data cleansing, mapping and data management (with an eye toward compliance with GDPR, of course).
A centralized customer repository is the core of every machine-learning algorithm. There should be no data gaps in collecting and integrating customer data. The actionable data are often very granular, including details of purchases made, products viewed, carts abandoned and so on.
Today, retail has become a customer-focused business. Marketers who have built a solid data-driven culture and live by the “Analyze, Personalize, Repeat” mantra can only adapt to the ever-changing capabilities and expectations.
Opinions expressed in this article are those of the guest author and not necessarily MarTech Today. Staff authors are listed here.
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