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Putting a Face on Every Customer

By Jay Henderson, Director IBM Marketing Cloud, IBM Commerce

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Jay Henderson, Director IBM Marketing Cloud, IBM Commerce

Many of us have a favorite business that we visit all the time—for me it’s the local bakery. At these places we are regulars and with that badge are treated to extra personalized experiences.  The staffs know us, our specific preferences (large coffee with just a dash of skim milk) and needs (a seat away from the sunny glare of the window).

“By understanding their customers, marketers can become a valued partner who engages them at the right time and place with content and deals that are most relevant"

Unfortunately, these truly outstanding personalized experiences are few and far between when it comes to our interactions with larger businesses. But in the age of data and automated personalization, it doesn’t have to be that way. At any given moment in time, millions of people are online sharing their explicit preferences (e.g. what music we like or a person’s fashion preferences) and implicit behaviors (e.g. a consumer’s penchant for shopping online when timely and relevant deals come their way). But this information isn’t just being tossed into the ether on a whim. Today’s savvy consumer has become increasingly prudent in regard to what information and preferences they chose to share and they do so with great expectations.

Expectations of what you ask? When a consumer tells a brand what they prefer they demand to receive personalized engagements across any channel at all times in return. Consumers have little to no tolerance for brands that cannot deliver on this promise and there are many who fall into this category—according to a study IBM unveiled earlier this year with Econsultancy, four out of every five customers say that brands don’t know them as an individual. 

Despite this figure there is an opportunity for all brands, regardless of size, industry, or location, to personalize unique experiences in real time for each individual at scale. First they must harness the information that is being shared with them, then turn that data into insights and finally use those insights to engage customers with personalized content, offers and messages. Teams must also be prepared to personalize interactions in the moment, perhaps in reaction to a shopper’s sudden change in preferences or location. At first glance this may appear to be an overwhelming undertaking when you look at just how much data is being created but that is not the case.

Not sure where to begin? Pick a set of customer data, break it into different types of segments and look for common threads or outliers at the intersection of a segment, a channel, and your marketing messages. This requires analytics. There are a variety of analytic techniques and tools that must be used, each with a specific purpose and implemented at different times across customer interactions. Today there are analytics used to understand a customer’s journey, examine a person’s experience with the brand, assess their response to a particular marketing message, and improve the performance of marketing spend. Using these innovations, businesses have a chance to understand their customers on new levels while creating campaigns that deliver on their fullest potential.

With analytics you can answer questions about your customers and gain insights such as:
•What are they interested in right now?
•What are the interests of others similar to them?
•How do they buy?
•What frustrates them?
•What gets them energized and drives them to take action? 
•What are they saying about your brand in their social circles?
•Where are they are most engaged with the brand? Is it in store or on their smart phone?
•Where are they least engaged and why?

Just take a minute to consider the types of experience you can provide customers when you have this level of insight. Now add the ability to then deliver these campaigns, not just to one person but millions of people—a process that is impossible to achieve manually.

Here’s an example. A customer service team can monitor a shopper’s journey and examine their behavior as they access their site through their smart phone and their tablet. What could they find? Perhaps they could identify a pattern where the bounce rate is far higher on the smart phone and after taking a deeper dive discover that certain product images are not displaying properly on the phone when it’s horizontal instead of vertical. This has customers jumping ship well before they have had a chance to even consider taking any type of action.  This is clearly a missed opportunity, but with the one-two punch of analytics and marketing automation you can immediately connect with customers who were victims of this glitch and re-engage them before it’s too late.

Forward thinking retailers are starting to use cognitive analytics to personalize the in-store experience.  For example, in-store associates might use a clienteling app that would not only allow them to access valuable customer information (their favorite color, size, past purchases, etc), but also use that information to make recommendations about how to approach the customer, what to say to them, and what merchandise to direct them to Retailers can also combine micro-location technology and marketing automation to deliver push notifications when a loyal customer enters a brick-and-mortar store—containing personalized offers that could include anything from a discount to a "thanks for stopping by" message.

At a time when consumers have become more empowered, marketers do not have to give up the reign—they just need to add powerful analytics and marketing technology to the playbook. By understanding their customers, marketers can become a valued partner who engages them at the right time and place with content and deals that are most relevant. Marketers can add those personal touches that will resonate with consumers just like the staff at the corner bakery does for me (large coffee with just a dash of skim milk).

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