Month: July 2019

What do your Consumers Want?

Do you…

  • drive a 1990 Audi station wagon?
  • eat only rice and beans?
  • wear only hand me downs or clothes bought at your local thrift store?
  • only buy furniture at flea markets?
  • live in a van down by the river?

Probably not.

If someone asks you what you want for your birthday do you tell them shampoo or toothpaste?

Maybe, but that would be a rare consumer and a very strong outlier in any data set. And while that consumer wouldn’t require much effort when it comes to marketing strategy your potential and existing customers don’t just purchase the basic necessities to get by. They also purchase what they want.

A good marketing strategy starts with understanding what motivates buyers, allowing them to experience those feelings in advance, and thus creating a desire for them to take action.

How do you tap into that?

A good place to start is with data and lots of it. But, not just any data. There is an explosion of readily available data in this day and age from multiple sources, in multiple formats, and spread across multiple data silos. First, it needs to be cleaned & unified.

From there you need to optimize your data through segmentation, profiling & modeling, and personas while combining spending habits, touch-point behaviors, and other various measures into one single reliable customer view.

This helps create new insights and intelligence that you can add to your campaign execution.

Don’t let your marketing strategy be a one size fits all approach to just spray out a message hoping it will land on someone who will buy. Make it a goal to understand the wants and values of your potential and existing customers. A good place to start is always with clean, unified, and optimized data.


360-Degree View of a Customer

If you are like most companies, you have switched software vendors multiple times. And you probably still have multiple different software systems that you still use. Your data is siloed. This challenge is super common.

Data Hygiene and Identity Resolution is the beginning of the fix to this problem. Data must be cleaned in order to bring it together and create unique persistent pins. But that’s not the end result of this process.

Once you have clean and merged data you are left with a 360-degree of a customer, a holistic view of spend measures, buying habits, and consumer traits.

But why is this important? By analyzing the past and present interactions of a customer, you can use predictive analytics to shape the future. Will the consumer respond to cross-sell opportunities or upsells? A 360-degree view of your customer will help you figure that out.

A 360 view can also aid in the creation of customer personas. Knowing what your customer looks like will help you build an effective marketing strategy and campaigns. You can target your client base with a much more personalized feel.

With a more personalized customer experience, you can build loyalty. And brand loyalty will drastically increase the lifetime value of a customer.

Don’t guess at what your customers look like. Know for sure with a level of depth and insight that will keep them coming back.

Customer Retention is Key

Lost customers can result from being overlooked, not getting enough attention, or getting too much attention. It can ruin customer relationships or how they perceive your brand. Companies need a platform to engage their customers personally across all touch points on a regular basis with the right message at the right time.

Whether it’s quarterly, seasonal, monthly, weekly, or promotional outreach, it’s imperative that companies retain customers against multiple competitor campaigns.

Be sure to reinforce the value of your brand, respond quickly to any real or perceived problem, and get proactive in knowing your customers base. Start with profiling & modeling, segmenting your customers, and creating personas. See how customers rank along multiple factors including revenue contribution, lifetime value, and campaign response rates then take a closer look at how often and in what ways you are connecting with them.

How often are you contacting your customers (too much, too little, not at all), through what channels, what is the purpose of your outreach, what messaging are you using, and what are historical outcomes of those interactions?

Put yourself in your customers shoes. Do your outreach efforts make you want to buy more from your company, feel valued as a customer, feel like your preferences and buying habits are understood?

Apply analytics to your data to better understand your situation, then decide on the frequency, purpose, and channel of outreach to stay top of mind to your customers before they go elsewhere.

Stay on top of your Data Hygiene

In today’s “Big Data” world most business decisions are data driven but the smart and accurate decisions start with clean data.

Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. (wikipedia)

Having clean data is important in every department across B2C and B2B organizations especially in marketing. Some of those multiple data points are:

  • Address Standardization
  • Address Correction and National Change of Address
  • Email Validation
  • Phone Type Validation (Mobile vs Voip vs LandLine vs Company # vs Direct)
  • Duplicates
  • Missing or incomplete data


Bad data can be worse than no data and lead to problems with cost, wasted employee productivity, and customer distrust. For example:

  • Poor data quality is also hitting organizations where it hurts – to the tune of $15 million as the average annual financial cost (Gartner)
  • 77 percent of companies believe their bottom line is affected by inaccurate and incomplete contact data and on average, respondents believe 12 percent of revenue is wasted. (Experian survey)
  • Bad Data Costs the U.S. $3 Trillion Per Year (Harvard Business Review)

With the increasing volumes of data, data sources, and technology stacks housing siloed data coupled with the increasing need to make better and more informed data-driven decisions it is becoming paramount that organizations stay on top of their data hygiene.