Does MailChimp Really Know Your Customer?

“A place for everything, everything in its place” – Benjamin Franklin

As the above quote goes, we have many solutions/products offering and operating in various niche areas even within the same business function and within the same industries. However, each of these fit perfectly well only to some. Don’t go by sound bites alone. When everything matches, you will see the difference.

I empathize sincerely with every organization, which is on the lookout for a perfect solution or Product that fits the best to its need, but get overwhelmed by the number of buzzwords, choices and products all sounding similar at the first sight.

Products that seem to pitch the “same thing” is overwhelming. Have you ever been in such a tricky situation?

Let’s see if it indeed is the “same thing”? or if it’s is it a brainteaser where scrambled words seem to sound the same way and give that effect of the perception of the “same thing”.

MailChimp has its place in email marketing for what it’s worth, but it’s not what an organization should be depending on, if the objective is to know your consumer and send personalized messaging for the most effective email marketing.

Let’s find out here.

Your customer data is in various systems by virtue of storing a variety of digital activities such as their purchase history, web visits, inquiry calls, general browsing of your website, and social media data for reviews, comments, and general brand perception to name a few.

Does your MailChimp or other related email marketing provider(s), incorporate all the customer data that you own?

If you knew the answer and it was ‘No’, please read on…

Think of it this way, your customer is yourself in disguise. I don’t mean to say it in spiritual terms but in the general, logical sense. Your business might be struggling to get the right attention of your consumer so a sale happens. But wait a minute! Aren’t you also a consumer of some other product to someone else? Have you seen them succeeding in getting your attention? If so, how, and if not so, how can you do it?

It’s simple in thought and concept at least. Now you might be able to understand better why your customer’s attention is hard to get and what it takes to target precisely.

Good, “A problem well defined is a problem half solved.” — Charles Kettering.

Let’s change our focus for a second and swap the roles with your customer for a thought experiment. Now, you aren’t a merchant trying to sell something to anyone but you’re a consumer of some product. As a consumer, you’re trying to understand which of your vendors have truly gained your trust, appreciation and credibility by selling you something opportunely and that which caught your attention clearly. If you trace back to your personal stories of various instances, you will arrive at some place where it leads you to one of the cases at a high level.

1. I generally looked for promotion type X + category type Y (food, movies, recreation, electronics, pets, gifts, etc.) + products/services that are closer to my place (and many more precise details).
2. I always open a promotional email if it is during my office hours and not during weekends or off hours (or some other definitive pattern).
3. I am generally attracted to a promotional email offer that coincides with some context, event and message.

In a perfect world, we could gauge how and what would make us click any email that lands up in our inbox, and if you as a consumer would buy or not.

But we are not biological robots. We are conscious beings with some irrational emotional play into our decisions. Going by the quantitative analysis and/or leaving behind the strong digital footprints will not help even when demographics are factored in.

Let’s break this down.

What if the Brand you like, bombards you with offers and spams your inbox? Doesn’t it frustrate you and stretch you to fatigue? Do you not wish the company knew some basic information/purchase patterns/behaviors about you, as you have been a loyal consumer for many years?

Predictive analytics based on machine learning algorithms for cluster classification and individual customer insights play a significant role in personalized messaging for email marketing: A few or many of the keywords might match with others are saying? Yes, the keywords and the sound bites all match and look familiar to many of us. The data treatment, data completeness and comprehensive incorporation can potentially change the predictions altogether.

There are four different types of analytics: conventional reporting, business intelligence, predictive, and prescriptive. They are all very different and their purposes are even more pronounced.

1.  Conventional reporting plots your data history.
2. Business intelligence analytics applies quantitative analysis and ability to the show slice and dice of data.
3. Predictive analytics comprehensively captures all the relevant data. Data mined for both quantitative (recency, frequency, monetary value, timing they typically click, click resulted into sale or not and dozens more) and qualitative analysis (rich attributes for demographics, lifestyle habits etc., for personas/behaviors/motivations)
4. Prescriptive analytics is based on the predictions in recommending how you should package your product categories/assortments/associations, what products to feature based on individual customer predictive insights, who to target in your next campaign etc.,

So, what makes predictive and prescriptive analytics so unique and promising?

We must look at some basic, common sense ideas. If you take only a narrow slice of your consumer’s data, apparently, you are not doing enough to target with any precision by any dimension. But, if you take all the relevant data points of your consumer’s touch points with you wherever they occurred, and however you have stored them, you have a high chance of knowing your consumer interests better. Knowing is the first step to predicting.

If you have at least five or six categories to capture and analyze your individual consumer’s journey pattern, why are you trying to analyze only from email transactional data? Why are you leaving behind the rest of the signals? Food for thought.

MailChimp or its adjacent vendors are email marketing service providers who blasts the emails to a list of consumers. Over a period, they have collected metrics after the email was sent. For instance, they might have captured the questions of what all happened to my email note after I sent to each consumer:

1. Who opened when at what time?
2. Click happened or not?
3. Time spent?
4. Bounce rate?
5. Products (individually if featured) click metrics.
6. “Unsubscribe” clicked or not?

And maybe a few or many more in the similar scope. Your MailChimp’s and/or its adjacent vendors’ email metrics become yet another transactional data that you captured and analyzed. But is it enough to gauge your consumer’s interests and all qualitative aspects just by mining into only the email transactional metrics?

If you as an organization are interested in knowing your consumer’s journey as a whole, MailChimp and its significant others as a solution offer insights based on only a limited and narrow piece of your customer journey. It’s not complete, as it doesn’t consider your consumer’s entire digital footprint, and it isn’t enough to just combine with demographics with email transactional data as their purchase history and other interactions carry strong signals that might tell you a different story. Also, there is a sense of packaging the right set of products that interest your consumer based on what you offer plus what your individual consumer likes/dislikes.

In summary, if you’re looking to make the best use of your customers’ journey and all the digital footprints they left for you to make your email marketing the most effective method to gain/retain your customers’ trust, appreciation, and respect along with increasing your sales potential, then MailChimp and related others aren’t the best predictive marketing for you. The email transactional data metrics you collected using MailChimp or others become yet another data source that should be used in looping back for input into your predictive and prescriptive analytics.

Your business should consider predictive marketing that encompasses all the customers’ journey and by doing so, you will have the best foot forward in winning your customers’ trust and appreciation with even a high chance of advocacy to your products. You’d have given the necessary human touch despite the millions of customers you might be managing for every email campaign.

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About Author: Veda Konduru is the CEO and Co-founder of VectorScient. She is a passionate, startup entrepreneur who dreams big on helping the society and communities at large by providing high value predictive intelligence products, strengths in Artificial Intelligence. Veda offers broad-based experience providing excellence in technology and business leadership. She has several years of experience and expertise in sales, demand planning and supply chain applications. Veda has demonstrable expertise in product architecture using machine learning (a branch of AI), data science. She is adept at breaking down complex, abstract problems into simple, sizable, tangible, actionable components. Veda is a strong advocate for developing content that explains a complex problem or algorithm in simple, relatable daily life activities and events.