How to leverage Predictive Marketing for eCommerce brands
Just like other marketers, have you been through the saddest part of not seeing the expected results after months of working on a marketing campaign?
Marketers dedicate their creative efforts, time, and various resources to a campaign that seemed to be beneficial but had landed nowhere near the anticipated ROI or customer engagement.
Hence there’s a strategy that could take the marketers closer to what could be expected with Fashion Ad Marketing Campaigns before they run it.
Yes! You heard it right…
The rise of Big Data and Artificial Intelligence has empowered marketers with more powerful analytics tools than ever before. Such as, data-backed consumer insights can be used to intensify marketing efforts at each stage, and one of the most effective tactics is using predictive analytics.
Marketers have perfectly utilized data to concede and develop their marketing campaigns’ effectiveness. However, technology as a leading force has taken these efforts to the next and more advanced level.
Marketers embraced media mix modeling (MMM), which is a method of data-driven marketing. It allows the understanding of the long-term consequences of a campaign had on sales and to optimize the efforts accordingly.
As data-driven marketing has emerged, marketers across the globe today, now possess the ability to leverage a new and effective marketing tool: Predictive Analytics.
Predicting your customers’ subsequent actions is no longer a fictional move. Rather, predictive marketing is popular and more plausible than ever before.
In this article, we’ll run you through what predictive marketing is, why Fashion eCommerce Marketing stores need it, best practices for implementing it for better marketing performance, higher ROI, and, ultimately, faster success.
What is Predictive Marketing?
Predictive marketing is assisting marketers in a big way, and it’s only going to be more prominent. According to the State of Predictive Marketing Survey report, 91% of top marketers are either fully engaged with or already implementing predictive marketing.
If you haven’t heard of it before, probably, you may be wondering what it’s all about.
Certainly, you may relate predictive marketing with the latest technologies such as Machine learning assistance, the influence of artificial intelligence, or big data science.
“Predictive marketing is a branch of advanced analytics that governs big data to predict future outcomes of a marketing campaign”
Predictive marketing utilizes data correlated to audience behavior, consumer past research, buying history, website analytics to help predict marketing results. It involves various procedures such as data mining, statistics, machine learning, and artificial intelligence to prepare and analyze multiple data sets to develop future predictions.
There are three types of models that leverage predictive marketing:
Cluster Models: These models are used for audience filtration based on past brand engagement, past buying data, and demographic data.
Propensity Models: These models judge a consumer’s possible action such as will it convert or act on an offer or simply disengage.
Recommendations Filtering: These models offer recommendation models for consumers by analyzing past purchase history to know where additional sales opportunities exist.
How marketers incorporate Predictive Marketing Analytics to enhance marketing:
- Predictive Lead Scoring
Lead scoring is recognized as one of the fundamental marketing automation tasks for targeting the right customers and prospects in order to enhance the productivity and efficacy of a marketing campaign.
Whereas predictive lead scoring directs the traditional lead scoring method to the next level by leveraging big data and machine learning algorithms to evaluate the vital customer behaviors and rank them on a scale to identify the ones who are more likely to convert, retain, or buy.
Predictive lead scoring minimizes the element of human error and strengthens the accuracy of classifying quality leads. Predictive lead scoring employs predictive modeling which is a general statistical technique practiced to predict future behavior based on past behavior.
Key takeaway: Leveraging Predictive lead scoring, marketers could come up with an exemplary profile of a customer that is most likely to convert, based on the infusion of historical demographic and activity data. Thus, it makes it easier to identify the warmest leads.
- Predictive Product Recommendations
Nowadays it has become essential for nearly every eCommerce fashion brand to utilize a product recommendation system. Certainly, these systems can significantly elevate revenues, CTRs, and conversion rates of the brand.
Also, it can considerably enhance the user experience as well.
Predictive marketing incorporates filtering tools that work on the algorithms and data to suggest the most relevant products to a specific user.
“The first in personalization, will be the one dominating the eCommerce category”
(Peeking in the past)
Amazon founder Jeff Bezos realizes the value of recommender systems and adopted personalization in eCommerce way back in 1998:
Whereas the Accenture Pulse Survey suggests that 91% of online shoppers prefer the brand that recognizes, remembers, and provides relevant offers and recommendations.
In the contemporary competitive era, applying such techniques has become a necessity for the successful operation of an online business.
Also, studies suggest that 35 percent of the total Amazon revenue and a whopping 75 percent of what people watch on Netflix come from product recommendations.
- Open email prediction
Email is the chief essential channel to communicate with the customers for a few companies.
Where the average rate of an email campaign should be 15-25%, why not ensure that customers are being kept engaged via emails, and the integrity of your email campaign is maintained?
Open email predictions, however, will reveal whether a customer will open your next email or not.
Predicting email opening determines the likelihood of a customer opening an email, and the aim is to approach the most interested customers first, rather than spending time and money on the uninterested ones.
An example from the ZlavaDna, who have tested the email newsletter campaign as rather targeting all audiences, should only approach engaged customers.
Hence, with the use of predictive analytics, customers were scored on the basis of the on data including their previous open rates, recent web activity, and the comparison of other similar customers.
The score was further used for segmentation and the frequency capping was implemented for each segment and the company only targeted 20% of the customers with the highest possibility of getting engaged. This move has minimized the amount of customer that has been targeted and has maximized the overall impact of email sent to each customer.
The company has sent 1 million emails with a whopping 4 times higher open rates and 3 times higher click-through rate and generated the same revenue as it was being generated by sending 4.5 million emails.
- Customer churn prediction
A great customer experience is ought to be the most effective aspect for successful business growth. However, it’s pretty difficult to tell when customers need new content and when they are about to churn quitely.
Surprising though it may seem, but only about 1 out of 26 disappointed customers complain, the rest 96% churn silently.
That’s why it has been necessary for the companies to implement predictive marketing strategies to identify and re-engage the customers that are about to churn.
To illustrate, a renowned mobile phone company, Sprint has encountered a high churn rate. The marketers have quickly adopted predictive analysis to determine which consumers are probably gonna cease their service plans.
Upon successful identification of such customers, the company had targeted them with re-engaged communications, messaging, and special offers to enable them to keep up their services.
The predictive strategy adopted by the company has resulted in a 10% decrease in customer churn, and an 800% uplift in upgrades within 90 days of implementation.
Now that you have a fair idea of various Predictive Marketing strategies, now have a look at a few associated benefits.
Predictive Marketing benefits for an eCommerce brand:
Owing to the several advantages, the Predictive market is supposed to be a $10.95 billion market by the end of 2022.
It assists brands to have an edge over their counterparts
The usual rationale behind predictive analytics practice is to gain insights about the popular trends in the market to get a competitive advantage. Since customer buying patterns and trends keep on changing from time to time, thus, it’s vital that who will identify those trends first.
Likely, if you want to gain the forward steps of your competitors, you need to inherit predictive analytics, today. This strategy will not only assist in generating more qualified leads, but predictive analytics also enables brands to get a perfect vision into their current and prospective customers.
Elevates Business Growth
As predictive analytics aid the brands to predict customer’s preferences, buying behavior, and responses, therefore they will be able to entice their target audience and transform them to become loyal customers.
Predictive analytics is a proven tactic that facilitates brands with useful information about their customers. For instance, which customers are likely to churn, what strategies you could adopt to retain such customers, whether or not you should put your customers in the direct marketing campaign, and more.
Satisfying Your Customers
Retaining current customers and acquiring new clients by investing as much time and money is the key determinant for a successful company.
The fact says that procuring a new customer is about 5 times tougher than retaining the ones the brand already has.
Certainly, there is a need to commit serene marketing strategies for your existing customers to retain their engagement with your brand. Predictive marketing is a proactive approach to plan your marketing strategies for such customers and urge them to visit your eCommerce store frequently.
Leverage Previous Customer Data to Make Smart Decisions
Just because it is vital, most of the renowned companies peek into the past performances of their business and analyze past customer data to develop precise marketing strategies. Also, it is essential for brands to examine the errors made in the past.
Predictive analytics, therefore, is an effective technology that strives to assist companies in predicting the outcomes of their future marketing strategies based on past performances.
Fundamentally, it’s all about learning from your former marketing actions. This data benefits brands to structure accurate marketing plans.
Provide Personalized Services
The one-size-fits-all approach is a thing of the past.
Today, audiences seek personalized attention and you should be prepared to serve their needs via personalized marketing campaigns to garner the attention of your target audience.
Literally, no one prefers to spend time opening their emails to read the common sales-related message. People favor brands that offer personalized services.
Predictive analytics renders you with data concerning your customer’s expectations, their past purchases, their browsing history, and purchasing patterns.
Marketers usually leverage this data to form personalized marketing tactics that feed their specific demands. Despite retaining the engagement of your existing consumers, personalized services also aid in attracting a new audience as well.
Certainly, predictive analytics is a perfect aid to successful marketing campaigns. It blends the association between data metrics and more reliable business results with excellent strategies to bring more influence across the customer journey map.
However, it should not be forgotten that implementing Predictive Marketing strategies demand a strong knowledge of marketing analytics metrics to be an appropriate foundation for modeling structures and scoring categories.
Given the exceptional advantages, it’s unquestionable that employing predictive marketing procedures will help eCommerce brands maximize their marketing goals, and increase their sales potential.
Does your existing marketing system offer organized data to help your business grow faster?
You’re probably marketing with an inadequate customer data profile, whereas the insights provided by predictive analytics could be assisting the decisions made by your competitors.
Netgains supports various renowned global brands in leveraging their marketing strategies to drive more sales with super-targeted, highly relevant marketing campaigns.
Since 2004 Netgains has been building fashion e-commerce website & running effective fashion digital marketing campaigns for fast-growing as well as established fashion brands. Our expertise in fashion eCommerce ensures that your brand and products are delivered to your customers in a way that makes them buy. Get in touch today!