Video and Business Strategy
Sections in Chapter 6:
How to understand consumer behavior and incorporate it into business strategy.
The implications of daily conversion data and order value data on campaign strategy.
How to use repeat purchase behavior and customer lifetime value to guide strategy.
Consumer Behavior Seasonality
Seasonality does not only apply to certain businesses with seasonal products but it also applies broadly to consumer behavior. Depending on the location of a target audience, overall consumer behavior can change significantly over the course of the year (e.g. increased consumer spending preceding a holiday season). Seasonality not only impacts conversion volume, but also the average time it takes a consumer to convert and is an important factor that should be considered when launching a campaign.
One way to analyze consumer loyalty is compare consumer lifetime value and see the relative value of different consumers over time. Consumer lifetime value, however, does not reveal the cost of consumer loyalty, because some consumers may make an initial purchase and revisit a website and make repeat purchases on their own accord (these are inexpensive loyal customers) while other consumers will only make repeat purchases if they are retargeted in subsequent ad campaigns (these are expensive loyal customers). The best way to determine the efficiency of consumer loyalty is to calculate each conversions value relative to ad spend (COAS) and apply this metric to consumer lifetime value to create an index of consumer loyalty.
Consumer Conversion Metrics
The most important consumer conversion metrics are total impressions to convert, total clicks to convert and average time to convert. The total number of impressions it takes to convert a consumer measures consumer behavior from initial impression to the first website visit all the way through to the final conversion and indicates the quality of the campaign’s creative content. The total number of clicks it takes a consumer to convert is a similar metric that indicates the quality of a campaign’s creative content and also the degree of consumer engagement. The average time it takes a consumer to convert reveals the quality of the website and the effectiveness of the product description.
Historical Consumer Behavior
A number of records of historical consumer digital advertising behavior create a clear roadmap for predicting future advertising behavior. While personal information on consumer purchase history prior to the launch of a campaign is legally inaccessible, all behavior after the launch of the campaign is compiled and factored into the campaign. Furthermore, general information about a consumer’s history, such as whether they have shopped online, interacted with digital advertising or clicked on digital ads in the past. Information about a consumer’s device preferences, ad type preferences and ad duration preferences are all recorded during a campaign and are used to optimize campaign performance.
Full-funnel attribution tracking provides rich insight into consumers’ digital advertising behaviors in response to the digital advertising to which they are exposed by supplementing website data with the cross-channel consumer conversion journey. Full-funnel attribution tracking reveals how many impressions it takes for each consumer to convert and where those impressions come from, how many clicks it takes each consumer to convert and where those clicks originated and finally how many channels impressed each consumer and which of those were most effective.
Conversion Data and Business Strategy
Conversion Volume per Day and Campaign Success
The amount of traffic that a client’s website receives on a given day determines how quickly their advertising campaigns will see results and how rapidly they can scale their campaigns. The following list describes what businesses with variable levels of business can expect when their campaigns are launched:
Conversions Per Day
While business trends vary by industry and company, conversion volume is an important metric for all businesses to consider when allocating advertising budget.
(or fewer) daily conversions
This campaign size usually represents a new business or a business with a new website, so advertising efforts will generally focus on driving traffic to the website, building brand awareness and setting up a goal of future conversion. When traffic is so low, the average conversion length is very long and it is difficult to achieve a positive return on investment. This type of campaign is considered a high-risk because it is difficult to balance a budget that may be reliant upon conversions that won’t be realized for months of consistent expenditure.
This campaign size usually represents a small business that is spending a consistent amount of money on its advertising budget but positioning itself for future growth. Typically, a business in this category spends $1000-$1500 per month and will see a positive return on investment if it has an average order value that is over $50 (businesses of this size can expect a cost-per-acquisition of $150). This type of campaign is considered low-risk because small businesses of this size tend to be stable.
This campaign size usually represents a small but rapidly growing business that is experimenting with a larger advertising budget. When setting an appropriate budget for a growing business, it is important to scale the budget to match conversion growth and not vice versa. This type of campaign is considered medium to high risk because businesses of this size tend to be unstable and have unclear budgetary expectations.
This campaign size usually represents a growing business with an established marketing strategy. Typically, a business in this category will be using several stable marketing channels in concert. Businesses is in this category often start with small test budgets ($100-$1500) and then settle into monthly budgets that range from $5000 to $10000 and deliver a consistent 2-3x return on investment. This type of campaign is considered low-risk because businesses with a varied advertising portfolio tend to be stable and scale predictably.
This campaign size usually represents a large business that operates across multiple marketing channels but is trying to increase efficiency, decide which marketing options are most appropriate or eliminate overlap between channels. These businesses typically cycle through different advertising solutions very quickly and expect high performance on test campaigns to proceed. This type of campaign is medium risk because many businesses of this size discard advertising campaigns before they have been optimized.
(or more) daily conversions
This campaign size represents a large business that operates across multiple channels and has a stable marketing strategy. Businesses in this category often want to test the efficiency of their individual marketing channels or develop a clearer picture of their overall marketing performance. This type of campaign is considered stable because businesses of this size are typically stable and provide huge amounts of data for campaign optimization.
Additional Consumer Data Insights
Conversion data can reveal a business’ business trend, a model of business growth that can be used to measure and predict long-term performance and create a long-term budget allocation guideline. Conversion data also provides insight into a business’ conversion rate with a particular channel, which can be compared against conversion rates for other marketing channels. The conversion rate offers a way to level the playing field between several separate marketing channels and analyze them on more than their individual KPIs to understand which components of marketing strategy are most and least successful. Conversion data can also show what percentage of overall conversions for a business can be attributed to one individual channel. When plotted against budget allocated to each marketing channel, this information about conversion can reveal the relative efficiency of each individual marketing channel at driving conversion and suggest ways to reallocate overall marketing budget to increase efficiency or scale.
Average Order Value and Campaign Performance
Lower average order values correlate to higher cost-per-acquisition, higher consumer retention and larger lifetime value. As order value increases, the number of orders per day required to sustain a return on investment decreases. The chart below outlines the relationship between order value and orders per day for a hypothetical business with a $5000 monthly budget and a monthly goal of a 2x return on investment:
Extremely Large Order Values
Order values that are very large (particularly luxury products that represent a return on investment after a single sale) should be evaluated on a different scale than less expensive items. Additional analysis is necessary to eliminate the influence of randomness and perform in-depth long term analysis.
Extremely Small Order Values
Order values less than ten dollars rely on a very large number of new users driven to the website every day and a very high conversion rate. These factors are very difficult to achieve, and therefore campaigns for products with small order values tend to be more successful when targeting CPA goals instead of ROI goals. Products with such low order values must target consumers with high lifetime values and significant repeat purchase behavior.
Order Value Data and Budget
Total order value per day is a good guideline for setting an initial marketing budget. Clients with access to data about daily order values should set their daily marketing budget lower than their daily order values if they want to avoid losing money at the beginning of a campaign.
Order Value Data and Consumer Lifetime Value
Aggregated order value data can also help provide predictions about a consumer’s lifetime value. Consumer lifetime value is a powerful metric that can reveal consumer loyalty and be used to predict future return on investment and cost-per-acquisition. Consumer lifetime value data can also be compared against lifetime value data from other marketing channels to reveal the relative efficiency of each individual marketing channel at driving lifetime value and suggest ways to reallocate overall marketing budget to increase profitability.
Consumer Lifetime Value
Consumer lifetime value is an enormously powerful metric that can be used to shape long-term business strategy. To calculate consumer lifetime value, clients must be sure to established a standard window for evaluating consumer behavior and a standard window for new consumer conversion and repeat consumer conversion before extrapolating consumer behavior to predict future consumer value. Consumer lifetime value can be combined with the repeat purchase ratio both to guide imminent campaign goals and also to produce broader, high-level insights about brand loyalty and long-term budget planning.
Understanding repeat purchase behavior is crucial to maintaining campaign efficiency. Some repeat purchasers need persistent motivation and retargeting to drive conversion while others with greater brand loyalty will continue to convert unprompted. Differentiating these two groups is an important part of long-term campaign strategy because redundant retargeting of loyal customers can have a crippling effect on long-term advertising efficiency and performance.
To optimize campaign performance, it is important to understand and anticipate the contribution of consumer lifetime purchasing behavior and repeat purchasing behavior on overall conversion rates. Consumer lifetime value is a good way to understand the true value of a consumer but it is only valuable to short-term campaign performance when loyal repeat purchasers and lifetime customers are removed from advertising campaigns to avoid redundancy. Even though repeat purchasers and lifetime customers could factor into campaign conversion rates and inflate numbers, it is important to remove these consumers in the name of long-term efficiency and overall business growth.