LifeLock 2013 Annual Report Download - page 46

We calculate monthly average revenue per member as our consumer revenue during the relevant period
divided by the average number of cumulative ending members during the relevant period (determined by taking the average of the cumulative ending members
at the beginning of the relevant period and the cumulative ending members at the end of each month in the relevant period), divided by the number of months
in the relevant period. A number of factors may influence this metric, including whether a member enrolls in one of our premium services; whether we offer the
member any promotional discounts upon enrollment; the distribution channel through which we acquire the member, as we offer wholesale pricing in our
embedded product, employee benefit, and breach channels; and whether a new member subscribes on a monthly or annual basis, as members enrolling on an
annual subscription receive a discount for paying for a year in advance. While our retail list prices have historically remained unchanged, our average revenue
per member increased by approximately 11% in 2013. This growth was primarily driven by increased adoption of our higher priced premium services by a
greater percentage of our members, a trend we expect will continue. We monitor monthly average revenue per member because it is a strong indicator of revenue
in our consumer business and of the performance of our premium services. The increase in our monthly average revenue per member resulted primarily from
the continued success of our LifeLock Ultimate service, which accounted for more than 40% of our gross new members in 2013.
Our monthly average revenue per member for the year ended December 31, 2013 was $ 10.32, an increase of 11% from the year ended December 31,
2012.
We calculate enterprise transactions as the total number of enterprise transactions pro cessed for either an identity risk or
credit risk score during the relevant period. Our enterprise transactions are processed by ID Analytics, which we acquired on March 14, 2012. Accordingly,
the enterprise transactions data includes transactions processed by ID Analytics before the acquisition. Enterprise transactions have historically been higher in
the fourth quarter as the level of credit applications and general consumer spending increases. We monitor the volume of enterprise transactions because it is a
strong indicator of revenue in our enterprise business.
We processed 216.7 million enterprise transactions for the year ended December 31, 2013, a decrease of 5% from the year ended December 31, 2012.
The decrease was primarily driven by a large telecommunications customer who had previously obtained scores for all their incoming subscribers through all
channels such as wireless, landline, and bundled internet services. After process and technical modifications were made, the customer made the decision to
stop obtaining scores for in-home service customers due to the fraud risk associated with these segments being lower than the wireless segment. Going forward,
this customer will now only be obtaining scores for customers coming in from the mobile portion of their business where the fraud risk is much higher. Due
to the low per transaction price for this customer, this change had an immaterial impact to our enterprise revenue for the year. We do not expect to experience a
similar decrease with other existing telecommunication customers. In addition, we have seen a reduction in enterprise transactions as we gave notice of non-
renewal to several customers in our consumer segment and we have allowed such contracts to lapse as a result. We expect the transaction volume for these
customers to decrease as these enterprise customers churn over time. We do not expect this to have a material impact on our total revenue.
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