Ben Morris: Big Data For The Little Guy

You know what small entrepreneurs love to do? Steal the secrets used by cocky international corporations… and put that magic to work for the little guy. Ben Morris & Colin Chung of Kristalytics are our secret weapons here, finally delivering the almost SCARY “cost-slashing, results maximizing” mojo that Fortune 100 companies rely on through fancy “customer targeting” sci-fi level software… at a tiny fraction of the cost the monsters shell out.

Pay attention: You’re about to learn how to identify and reach the BEST customers you’ll ever find, locally and globally… even though, right now, they are HIDDEN from you. This is a peek behind the MegaBuck Corporate world of unfair advantages… and a chance to scoop them at their own game. Even if you’re working from a kitchen table. (HUGE results await…)

2:54: Little Guy = Smaller then Fortune 100. Not real small businesses.

Big data works for any BtoC product because it enables you to understand what your customers want.

People have regular, ongoing habits. There are patterns adn this allows you to sell them other things.

Political candidates use big data every day to win elections.

5:20 He gives specific examples about how policital parties and retailers use big data. The DNC credited access to big data for their win in 2012.

11:30: Why aren’t demographics enough? People with the same demographics don’t necessarily have the same buying habits. Your target can be refined using these characteristics.

Psychographic info examples:

Lifestyle clusters

Heavy Transactors: Heavy transactors buy almost anything they are shown, so are better to market to.

Discretionary Income: Most consumer products are discretionary, so it is good to market to ones who have the means to purchase.

Technodoption: The type of technology they have may affect what type of media you show in your ads.

Urbanicity: Exurbs vs downtown. Ie even though cds are going out of fashion, they may still be sold to those with long commutes.

17:25 Psychographics can accurately predict customers’ lifetime spend

• 500 Index: $500 spend
• 200 Index: $200 spend
• 20 Index: $20 spend

25 fold variance from 20 index to 500 index. If you know what a person’s index is, you can aim your marketing toward those who are most likely to spend more with you.

500 index tends to sell themselves, because buying is natural to them.

Psychographics allow you to judge targets based on their potential to spend rather than their history of spending.

25:00 The Big 4 Psychographic Universal Adapters

• Discretionary Income
• Heavy Transactors
• Economic Stability
• 70 Lifestyle clusters

Top 20% of Heavy Transactors account for 50% of discretionary spending

25:27 He shows a chart which illustrates the wide disparity of ROI between customer clusters. It was a losing campaign because they didn’t target it correctly.

Big data can isolate the portion of a list that is most likely to buy.

28:05 Frequency sells. Only 8% of likely buyers will buy within a given month

29:13 He shows a chart that shows how much you can afford to spend advertising to people based on response rate and the amount that they will purchase when compared to the database as a whole.

Track who is responding to your email

31:50 They look at impressions for Google campaigns. He explains why this is helpful and how they use it to improve results in the campaign.

1. Go through your Google or Facebook Analytics.
2. Take a look at the data you are given and see how you can apply Ben’s analyses to your own customers.
3. Can you target better with this knowledge?

Link to Ben’s website.