Lifetime Value Changes for Catalogers

Let’s see what would happen to a cataloger if it were to adopt the database initiatives proposed in this chapter. To understand the change, let’s start with a traditional successful cataloger. This company has already put its catalog on the Web. It sends out 2,000,000 books every 6 months, at an in-the-mail cost of $2 per book. The company gets an overall response rate of 4 percent. Included in the mailing are 500,000 new names. These produce responses from 20,000 first-time buyers. We are going to trace the lifetime value of these 20,000 first-time buyers over four rounds (2 years). The average order size on the first buy is $120, of which the product and fulfillment costs are 40 percent. In the second-round mailing 6 months later to these 20,000 first-time buyers, the purchase rate is 40 percent and the average order size is $130. This rises over the next year to $150, and the purchase rate rises to 50 percent. Of the original 20,000 first-time buyers in round 1, there are 1800 who are still buying 2 years later. Meanwhile, of course, the company has proceeded with additional prospect mailings that are producing identical charts every 6 months. The lifetime value of the original 20,000 first-time buyers after the fourth round is $67.68, as shown in Table 12-1.

Table 12-1 : LTV of Catalog First-Time Buyers

	Round 1	Round 2	Round 3	Round 4
Customers	20,000	8,000	3,600	1,800
Purchase rate	100%	40%	45%	50%
Average purchase	$120	$130	$140	$150
Revenue	$2,400,000	$1,040,000	$504,000	$270,000
Cost percent	40%	40%	40%	40%
Costs	$960,000	$416,000	$201,600	$108,000
Number mailed	500,000	20,000	20,000	20,000
Mailed cost	$2.00	$2.00	$2.00	$2.00
Mail costs	$1,000,000	$40,000	$40,000	$40,000
Total costs	$1,960,000	$456,000	$241,600	$148,000
Profit	$440,000	$584,000	$262,400	$122,000
Discount rate	1.00	1.04	1.08	1.12
NPV of profit	$440,000	$561,954	$242,963	$108,699
Cumulative NPV of profit	$440,000	$1,001,954	$1,244,917	$1,353,616
Lifetime value	$22.00	$50.10	$62.25	$67.68

Let us now assume that the cataloger has adopted many of the recommendations made in this chapter. The company has spent $1,200,000 on software for its Web site that does several significant things:

• Asks for customer profiles, capturing email names and customer preferences and demographics. This reaches 20 percent on the first round and an additional 20 percent on each additional round.

• Provides one-click ordering for all customers who complete the profile, along with personalized emails and Web site opening pages.

• Sends an email thank you for each order, an email when the order is shipped, and an email asking if the order was satisfactory.

• Provides personalized emails announcing the arrival of each book, with click here for items that it is assumed the customer is interested in.

• Uses collaborative filtering to make suggestions on next best product, leading to a cross-selling rate of 40 percent.

• Offers an advanced search feature that permits customers to find products faster.

• Has live shopper support for people who want to have a text chat with a customer service rep while they are on the site, or who want to call on another line to talk to a live agent.

The $1,200,000 software, amortized across 3 years, will represent a cost of $200,000 for each group of first-time buyers acquired ($1,200,000/3 = $400,000/2 per year = $200,000).

The result of these changes can be seen in the Table 12-2.

Table 12-2 : Improved LTV with Web Site Software

	Round 1	Round 2	Round 3	Round 4
Customers	20,000	10,000	5,500	3,300
Purchase rate	100%	50%	55%	60%
Average purchase	$120	$140	$155	$170
Revenue	$2,400,000	$1,400,000	$852,500	$561,000
Cost percent	40%	38%	37%	36%
Costs	$960,000	$532,000	$315,425	$201,960
Number mailed	500,000	20,000	20,000	20,000
Mailed cost	$2.00	$2.00	$2.00	$2.00
Mail costs	$1,000,000	$40,000	$40,000	$40,000
Software cost	$200,000	$0	$0	$0
Total costs	$2,160,000	$572,000	$355,425	$241,960
Profit	$240,000	$828,000	$497,075	$319,040
Discount rate	1.00	1.04	1.08	1.12
NPV of profit	$240,000	$796,743	$460,255	$284,256
Cumulative NPV of profit	$240,000	$1,036,743	$1,496,998	$1,781,254
Lifetime value	$12.00	$51.84	$74.85	$89.06

The purchase rate for the second-time buyers has risen from 40 percent to 50 percent. The average order size has increased. The costs have gone down as a result of increased use of the Web rather than telephone calls. Against that, there is a software cost for each group of first-time buyers of $200,000. Lifetime value has gone up to $89.06, from $67.68.

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Overall, the changes will increase profit by a total of $1.7 million over 2 years, as shown in Table 12-3. Note that these profits of $1.7 million include all costs, including the heavy losses in round 1 that resulted from the initial software costs.

Table 12-3 : Gains from Software Improvements

	Round 1	Round 2	Round 3	Round 4
New LTV	$12.00 $51.84	$74.85	$89.06
Old LTV	$22.00 $50.10		$62.25	$67.68
Difference	($10.00)	$ 1.74	$12.60	$21.38
Times 80,000	($800,000) $139,156	$1,008,323	$1,710,552

Each cataloger will have to work out its own figures based on its own situation. In the end, however, the results will probably be close to those shown here. When it is done right, database marketing works. Customer communications work. People respond when people they know and have done business with write to them and pay attention to them. Statistics from other catalogers discussed in this chapter show that when you adopt the improvements listed in this chapter

• The repurchase rate will go up.

• The average order size will go up.

• The cost of order fulfillment will come down.

• Cross sales will go up.

Building B2B Catalog Sales

A business-to-business cataloger with sales in excess of $14 million had never built a marketing database. It turned to Sejal Shah at CSC Advanced Database Solutions to come up with a plan. Here is what he found:

• The cataloger had about 55,000 current customers who spent an average of $250 per year.

• It mailed about 300,000 catalogs every quarter at $1 each and had an annual response rate of 6.2 percent.

• Its margin on product was about 53 percent, out of which it had to take the cost of the catalogs and about 10 percent for fulfillment.

Sejal recommended two methods for building sales with a database:

1. Building a customer database and using it to determine the profiles of the most profitable customers, then using those profiles to mail catalogs to companies whose profiles matched the profiles of these profitable customers

2. Using emails to communicate with customers, leading to increased cross sales, larger order size, increased frequency of orders, and increased retention

Creating Customer Profiles

The method that Sejal proposed was this:

• Once the database was built, append D&B data and use analytical software to determine the profile of the most profitable customers. Each customer profile would include these data:

  • SIC codes

  • Total purchases in the past 12 months

  • Key product groups purchased

  • Total employees and total sales

• Using this analysis, marketers at the cataloger could develop a market penetration report for each profile. The penetration report would look something like Table 12-4.

  Table 12-4 : Market Penetration

  Profile group	Company customers	U.S. universe	Market penetration
  A	10,221	109,334	9.35%
  B	8,874	99,447	8.92%
  C	3,341	45,331	7.37%
  D	2,116	69,004	3.07%
  E	1,984	83,556	2.37%
  F	445	4,801	9.27%
  Total	26,981	411,473	6.56%

This report clearly identified those companies that were the most likely prospects for further sales. Using these profiles, the company could acquire the names of prospects that matched the SIC codes and other data in the profiles.

Using these numbers as a base, what results could the cataloger expect from the prospect mailings? Certainly not the 6.2 percent received on the existing catalogs. Those were sales to existing customers, many of whom had been purchasing from this cataloger for years. Sejal estimated that with the new mailings, the cataloger would get about one-third of the sales rates that it got from the regular catalog mailing. As a result, he predicted that the cataloger would get a response in the first year from about 2 percent of those who received a catalog.

How many catalogs should be mailed? Sejal proposed three scenarios: a conservative, a bold, and an aggressive one. In the conservative scenario, the cataloger would mail to about 150,000 new names each quarter, or 600,000 during the year. The bold total would be 1 million per year, and the aggressive would be 1.6 million in total.

Putting everything together, Table 12-5 shows what Sejal projected for the results of the first year’s increased mailings. As a result of the new database and mailing strategy, the cataloger would gain between $3 and $7 million in sales, spend $200,000 for the database and software, and still make a substantial profit. Many companies expect to lose money in their first year of database marketing and recoup it later. This study shows that for this company, it was not necessary to predict a loss. Furthermore, this chart includes only new sales. Sejal assumed that the cataloger would also continue to get the existing annual sales of about $14 million.

Table 12-5 : First-Year Results

	Conservative	Bold	Aggressive
New mailing	600,000	1,000,000	1,600,000
Response rate	2.20%	2.00%	1.80%
New customers	13,200	20,000	28,800
Average order	$250	$250	$250
Revenue	$3,300,000	$5,000,000	$7,200,000
Name rental ($100/M)	$60,000	$100,000	$160,000
Catalogs @ $1	$600,000	$1,000,000	$1,600,000
Fulfillment @ 10%	$330,000	$500,000	$720,000
Database	$200,000	$200,000	$200,000
One-time DB costs	$140,000	$140,000	$140,000
Cost of goods (47%)	$1,551,000	$2,350,000	$3,384,000
Total costs	$2,881,000	$4,290,000	$6,204,000
Net profit	$419,000	$710,000	$996,000
Investment	$1,000,000	$1,440,000	$2,100,000
Return on investment	1.42	1.49	1.47

One-Time Setup Costs

In addition to the annual database costs, there were one-time setup costs, shown in Table 12-6.

Table 12-6 : One-Time Setup Costs

Needs assessment	$ 30,000
Design and development	$ 100,000
Training	$ 10,000
Total	$ 140,000

Email Marketing

Sejal projected that in the second year, the cataloger could gain from email marketing to its existing customers. The use of email marketing was possible only when the cataloger had a substantial number of customer records that included email names and permission to use them. Since the cataloger did not have many email names to start with, Sejal suggested that it become aggressive about capturing email names on all future sales, thus rapidly building up a base of customer email names.

What could be done with email marketing? Sejal suggested several techniques:

• Regular promotions of existing products, particularly before and after the catalog arrives

• Promotions of sale items

• Last-minute specials

• Retention messages (thank you for your business, customer surveys, etc.)

• Follow-up messages (thank you for your order; your order will be shipped on . . .)

• Viral marketing (“New product specs are available. Send them to a coworker.”)

• Email newsletters with product information

What results might the cataloger get from email marketing? The experience of other catalogers suggests a lift in sales of between 5 and 20 percent using well-targeted and appreciated emails. For this cataloger, Sejal conservatively projected only 5 percent. He used that figure to estimate the increased sales and profits from emails (Table 12-7).

Table 12-7 : Profit from Email Marketing, Year 2

	Conservative	Bold	Aggressive
Old customers	10,000	10,000	10,000
New customers	18,600	30,000	46,400
Total	28,600	40,000	56,400
Sales @ $250	$7,150,000	$10,000,000	$14,100,000
5% increase	$357,500	$500,000	$705,000
Profit @ 35%	$125,125	$175,000	$246,750

By adding the email profits to the prospecting profits, Sejal was able to predict the cataloger’s profits for the second year, as shown in Table 12-8. The second year’s response rate was projected to increase from 2 percent to 3 percent for a number of reasons. The first year’s mailing would show which SICs were pulling and which were not, so the cataloger should get much better at selecting names. In addition, many of the customers mailed to in the first year would be getting their second year’s worth of catalogs. Since the long-term projection of catalog response for this cataloger was 6 percent, these second-year customers should respond at a rate closer to that, bringing the average up to 3 percent or higher. The only surprise in the second year is the increased cost of the database. The software used in the first year did not include a provision for email marketing. Sejal recommended a software upgrade that moved the database cost up to $350,000 per year.

Table 12-8 : Second-Year Results

	Conservative	Bold	Aggressive
New mailing	600,000	1,000,000	1,600,000
Response rate	3.10%	3.00%	2.90%
Customers	18,600	30,000	46,400
Average order	$250	$250	$250
Revenue	$4,650,000	$7,500,000	$11,600,000
Name rental ($100/M)	$ 60,000	$ 100,000	$ 160,000
Catalogs @ $1	$ 600,000	$1,000,000	$1,600,000
Fulfillment @ 10%	$ 465,000	$ 750,000	$1,160,000
Database	$ 350,000	$ 350,000	$ 350,000
Cost of goods (47%)	$2,185,500	$3,525,000	$5,452,000
Total costs	$3,660,500	$5,725,000	$8,722,000
New mail profit	$ 989,500	$1,775,000	$2,878,000
Email profit	$ 125,125	$ 175,000	$ 246,750
Total profit	$1,114,625	$1,950,000	$3,124,750
Investment	$1,010,000	$1,450,000	$2,110,000
Return on investment	2.10	2.34	2.48

What this case study shows is how to go about calculating the benefits from database marketing. Too many people think that it is a nice concept, but have no idea of how to prove it.