Earlier today I received an email from a not-to-be-named retailer who outfits young urbanites in fashionable attire.  I agreed to complete a survey and honestly answered the first question of gender. The next page requested my age.  I again answered honestly, at which point a message popped up stating “This survey isn’t for you”.  After a few deep breaths I decided I wouldn’t be shopping there again in the near future.

This experience got me thinking about data - how it’s used as well as how it’s collected. Data should be used to improve customer engagement and their experience with your brand.  In order to use data successfully, the accuracy of the data must also be considered. Bad data can’t help you, it can only hurt you.

Behavioral Data

The most accurate data is data collected from a consumer’s actual behavior.  What did they purchase?  What website did they view?  What time did they log in?

Behavioral data can be the most accurate as well as the most useful.  There’s often no need to survey your customer about what they purchased because you already have the information in your systems.

The value of this data is that it’s based on facts, not sentiment.  When asking a consumer what they would want to purchase, they might be hesitant to admit their true shopping wish list.  If you ask me what I plan on ordering at a restaurant, I’ll say, “a kale salad with a light vinaigrette.”  My actual order?  Fried chicken wrapped in bacon with a side of mac & cheese. So when you send me an email, letting me know that you’re sending me a free offer for a kale salad… it probably won’t drive me to your restaurant.

When possible, data should be collected, not surveyed.  It should also be the key consideration when target marketing.

Demographic Data

However, behavioral data can’t determine everything.  Gender and age are still two key pieces of consumer data that factor into the billions of dollars spent annually on marketing.  Demographic data can be an important link in fully understanding a consumer. Yet, as important as this data is, it’s also difficult to ensure accurate demographic information is gathered as it is primarily self-reported by the consumer.

The below graph shows an interpretation of the trends we see in some loyalty data where some people are born in the future, and a surprising number born 400 years ago.

So what things need to be to considered when collecting  demographic data  in order to receive accurate, quality data?

What’s in it for them?

If you have plans to use age and gender in your marketing strategy then you’ll need to give your customers a good enough reason to give up the goods.

Consider offering benefits that are age and/or gender specific.  Or offering benefits only to those who fill out a demographic profile.  Let customers know that the data is private and will only be used to tailor communication to them. If they see value in what you are offering, they are more likely willing to share. The benefit being that the 45-year old male doesn’t have to bother receiving a “Ladies Night Out” promotional email.

Make the promise to provide relevant content and then stick to it!

What’s in it for you?

While demographic data can be deemed as secondary, or complementary, to behavioral data, it can be priceless when wanting to monetize your database - If you are interested in doing a cross-promotion the third party will often only be interested in age and gender.

When working in a bricks and mortar business, demographics become critical when looking towards growth.  If you know your current demographic and the demographics of your most profitable customers, you can find a new location for success where consumers of the same demographic are predominant.

Data quality dos and don’ts

You need to be strategic in how you collect the data you require from consumers.  Some best practices to ensure you are getting the most accurate data possible, include:

• Don’t set a default birth year in your system or you may be left wondering why your average customer base for your kids store is 75 years old
• Don’t collect this information via a free form table where date of birth can be 7/12/1980 or 12/7/1980 or July 12, 1980 or a number of other variations
• Don’t set a default gender in your system to a avoid a false gender bias
• Do make it easy for people to provide the information by using dropdown menus and radio button
• Do make sure customers are aware that providing their email address is going to be worth their while with exclusive and relevant offers

Contact Information

Now, for the grand finale. All of the data being you’ve collected could be for nothing if it’s not actionable.

Contact information, especially email information, is often poorly collected, leaving businesses with very little opportunity to directly market to their own customers.

Similar to age and gender, make sure customers are aware that providing their email address is going to be worth their while.  Send exclusive and relevant offers that can only be received via email or SMS.

Email collection dos and don’ts

Don’t collect verbally

• An “M” sounds like an “N”; a “B” sounds like a “V”
• No one wants to even try and understand how to spell Kealalio
• It’s too time consuming & difficult for all parties involved

Don’t collect manually

• Is that the number “0” or the letter “O”?
• You’ll get a lot of fake janedoe@person.com email addresses
• It’s too time consuming & difficult for all parties involved

Do collect online

• This allows the opportunity to put in follow-up checks to further validate emails prior to accepting

Do ask people to enter an email twice

• Some customers genuinely want to receive emails, but mistakenly mistype their own email address

Do include a syntax check

• You know that name@@gmail.com is not a valid email address, so don’t accept it

Do send a confirmation link to complete registration

Final thoughts

Wrong information results in inaccurate marketing and unintentionally poor business decisions. Data quality can be crucial to a company’s success.

Be smart about how you collect and use customer data. Make a promise that you’ll send relevant content, and they’re likely to share all the data you need to improve their overall experience.