Confessions of a Data Voyeur: From Curiosity to Better Decisions

Confessions of a Data Voyeur:

From Curiosity to Better Decisions

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Bundle.com is a NYC based start-up that uses data to help people make smarter money decisions.

Using data from billions of financial transactions, Bundle is able to show people decisions that others like them have made.

We believe that this data can lead to better recommendations and better decision-making.

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Further, we believe that decisions based purely on qualitative measures are leading to mistakes and bad decisions

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Today people are exposed to more new information in one day than someone in the

middle ages would see in their entire lifetime!

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What we heard…

“There is loads of information out there, but it doesn’t seem relevant to people like me..”

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So how do people make decisions when there is just too much information…

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They often turn to their networks and the environment surrounding them.

Whether it be

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…and they do so because peer comparison is part of human nature…for better…and for worse.

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…and while social media has had some success

….building relationships

….and building products

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In the end, does it only add to the

information overload problem?

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Are we past the point where people can make good decisions about where to spend their money, and more importantly, their time?

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What we heard..

“what I really want to know is what…not just anyone, but people like me are spending their [time and] money on…

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So we built a product that allowed people to see what others like them, their neighbors, were spending their money on..

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Bundle’s Everybody’s Money Data

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But we took it a step further and asked ourselves

“ What if you could see peoples actual experiences with merchants by analyzing their spending patterns?”

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And someone recommended Takashi…a restaurant on Hudson street not far from Bundle

So we did a little experiment….we were hungry…

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It was rated 4.5 stars on Yelp and 4 stars on Citysearch….it must be good….

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..and, of course, individual ratings were on both ends of the spectrum

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Restaurant Relationship Map

Standard NY

Balthazar

Spice MarketSmith & Wollensky

Saint Ambroeus

Daniel

Rosa Mexicana

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20

Actual Analysis for one NYC Restaurant (name not shown for

competitive purposes)

Merchant Intelligence Data – Customer Demo

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..and asked ourselves a question..

“What if we can see how often people actually go back to Takashi..

..what if we could give every merchant a score based on how loyal their customers are to them?”

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We created a Loyalty Score for Takashi

100

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As before, we took it one step further..

We scored every merchant in New York based on how loyal their customers are to them

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Numbers for illustrative purposes only

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Numbers for illustrative purpose only

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Getting to this point, however, has not been trivial

Transaction -> something that makes sense -> something that is useful

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Transactions level (aggregated and anonymized) financial data

US Government Data (Bureau of Labor Statistics, Dept of Labor, Census Bureau etc.)

Third party data (e.g. demographics)

Recommendations on optimizing your spending

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NYC TAXI MED 7M36 09LONG ISLAND C NY $17.70Mar 23

RYE HOUSE 0000000000NEW YORK NY $159.00Mar 22

ATTM*512015043468MNY ALPHARETTA GA $142.55Mar 20

COSTCO WHSE #1062 00NEW YORK NY $48.90Mar 20

TARGET T-2380 2380 NEW YORK NY $39.29Mar 20

MIYAKO SUSHI NEW YORK NY $62.94Mar 19

???

Transactions are not easy to decipher…

Do you recognize which merchants these relate to? Keep in mind that there are millions of merchants across the U.S.

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Analyzing and extracting relationships from billions of records is not easy…

 $a =~ s{[\W\s]}{}g;   $b =~ s{[\W\s]}{}g;   if ($a eq $b) { return 1;}  $a =~ s{^(THE|AN?)\s*}{}g;   $b =~ s{^(THE|AN?)\s*}{}g;   my $common_regex =

$common_words{$cat};   if (defined $common_regex) {       $a =~

s{$common_regex}{}g;   $a =~ s{[\W\s]}{}g;   $b =~ s{[\W\s]}{}g;   if ($a eq $b) { return 1;}  $a =~ s{^(THE|AN?)\s*}{}g;   $b =~ s{^(THE|AN?)\s*}{}g; 

 my $common_regex = $common_words{$cat};   if (defined

$common_regex) {       $a =~ s{$common_regex}{}g;    $a =~ s{[\W\s]}{}g;   $b =~ s{[\W\s]}{}g;   if ($a eq $b) { return 1;}  $a =~ s{^(THE|AN?)\s*}{}g; 

 $b =~ s{^(THE|AN?)\s*}{}g;   my $common_regex = $common_words{$cat};   if (defined $common_regex) {       $a =~

s{$common_regex}{}g;  $a =~ s{[\W\s]}{}g;   $b =~ s{[\W\s]}{}g;   if ($a eq $b) { return 1;}  $a =~ s{^(THE|AN?)\s*}{}g;   $b =~ s{^(THE|AN?)\s*}{}g; 

 my $common_regex = $common_words{$cat};   if (defined $common_regex) {       $a =~ s{$common_regex}{}g;   

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We continue to develop data oriented products that can help people make better decisions with their money and are eager to hear your thoughts

Email us at jaidev@bundle.com phil@bundle.com

To access the alpha version of our recommender, please sign-up at www.bundle.com

Thank You!