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NEW QUESTION: 1
In a Cinco ACI environment, which option bent dencriben "contractn"?
A. a net of interaction rulen between endpoint groupn
B. a Layer 3 forwarding domain
C. named groupn of related endpointn
D. to determine endpoint group membernhip ntatun
Answer: A
NEW QUESTION: 2
EC2インスタンスにデプロイされたアプリケーションがDynamoDBテーブルにデータを書き込むことを許可するには、次のアイテムのうちどれが必要ですか？
EC2インスタンスにセキュリティキーを保存することは許可されていないと仮定します。 2つの答えを選択してください
A. 起動構成に含まれるIAMロールでEC2インスタンスを起動します。
B. DynamoDBテーブルへの書き込みアクセスを許可するIAMロールを作成します。
C. DynamoDBテーブルへの書き込みアクセスを許可するIAMユーザーを作成します。
D. 起動構成に含まれるIAMユーザーでEC2インスタンスを起動します。
E. 実行中のEC2インスタンスにIAMユーザーを追加します。
F. 実行中のEC2インスタンスにIAMロールを追加します。
Answer: A,B
NEW QUESTION: 3
You are planning on uploading a list of 5,000 customers from the same country for a current client to build a custom audience.
What are some of the best practices you need to follow when uploading a customer database to build a Custom Audience?
(Select all that apply)
Choose ALL answers that apply.
A. Always include the country code as part of your customer's phone numbers.
B. Include only customers with highest value order for best performance.
C. Always include your customers' countries in their own column in your file.
D. Convert different currencies into the same one.
E. For customer lifetime value rate your customers on a ranking from 1-10
Answer: A,C,D
Explanation:
Explanation
The two most important tips are:
* Always include the country code as part of your customer's phone numbers, even if all your data is from the same country.
* Always include your customers' countries in their own column in your file, even if all of your data is from the same country. Because we match on a global scale, this simple step helps us match as many people as possible from your customer list.
What should I avoid when calculating customer lifetime value?
Different people calculate customer lifetime value in different ways. Here are some ways that you should avoid if you're going to send us the data for use in a value-based Lookalike Audience:
* Rating your customers. Say you have 3 customers worth $100, $10 and $1, respectively, and you use a
1-5 rating system. Don't send us data where they're rated as a 5, 2 and 1, respectively. This doesn't work because the value isn't proportional to the ranking. In other words, the $100 customer was factored by
20, but the $10 customer was only factored by 5 and the $1 customer wasn't factored at all.
* Ranking your customers. Say you have 100 customers and each one is worth between $200 and $1200.
You rank them from 1 to 100. This doesn't work because value isn't proportional here either. It tells us if one customer is more valuable than another, but doesn't account for a scenario where the number 5 customer is worth double what the number 6 customer is, whereas the number 20 customer might only be worth 1% more than the number 21 customer.
Important:
* Don't provide only your highest value customers. Instead, include a broad range. Without this range, we can't hone in on what might distinguish an average customer from a great one.
* Don't include negative numbers to denote negative value or undesirable customers. We can't use rows that contain numbers like that.
* If your value is in the form of a currency, make sure it's all the same currency or is converted to the same scale before uploading. We don't currently normalize for different currencies.
* Decimals that denote cents are acceptable, but don't use any other punctuation marks and/or separators.
We can't use rows that contain them.