Analysis objective 

This analysis will isolate the most expensive non-converting time periods of the week (whereby no purchasing cycles were catalyzed, attributed to or completed), and conversely will isolate the best performing time periods, both over the course of the day and day of the week on average.

From there a bid matrix can be constructed in Excel, to be implemented into the Google Adwords campaign settings. Google Adwords will then adjust all bids automatically, relative to how that time period performed historically.

Analysis: hourly performance

Every hour of activity for the example account between July 1st and November 17th 2013 has been aggregated and illustrated in the graph below, depicting the web orders driven versus the cost incurred. 

The blue and gold lines are last click and equally weighted web orders respectively. Equally weighted web orders are important to show when a purchasing cycle has begun, been attributed to, or completed – and is the key factor that makes this level of analysis rare and useful.

An equally weighted sale is credited evenly among all touch points that happened in the purchasing journey/funnel.  

In the graph below, the gold line illustrates a culmination of all the PPC proportions of each sale generated per hour from July to November.  

Last Click (absolute) web orders are important to show when a purchasing cycle has been completed via PPC. The greater the gap between the blue and gold lines, the more channels that have been involved in each sale over the hour.

By using both last click and equally weighted metrics together, we can see both the top level performance as well as a deeper level of insight, analysing the full impact each hour has over the course of the day.  

From the graph above we can conclude that:

  1. Between the hours of 5am-9am, and 4pm–6pm, this example PPC account hardly begins a purchasing cycle, or plays a part in one, or is attributed the last click before a web order – causing extremely high cost per web orders (see the icy blue mountain between 7am and 9am, or the volcanic red and yellow peak in the graph between 4pm and 6pm).
  2. Between the hours of 8pm and midnight the account drives a significant number of web orders (both in helping a web order to be generated and last click) for considerably the lowest cost per web order over the course of the day.
  3. Between 12 noon and 7pm, 60% of the total web orders are generated, and there is significant impression share (lost to rank) available for the account to grow into, through increased bids.

    However as the last click CPW is close to or just over £100 overall, and as CPA is of vital importance to this client,  leaving the bid adjustment at 0% – or even pulling back – would be recommended.

Google Adwords currently only allows six time slots over the course of the day, and so the hourly performance between July and November 2013 were aggregated into six separate four hour schedules.

After analysing performance over the course of the day, the following conclusions can be drawn with ad scheduling bid changes in the table below (from left to right – best to worst performing four hour slots in the day):

(please note: bid adjustments can be set from -90% to +900%) 

Analysis: day of the week performance

The next stage would be to convert this time of day performance into a bid matrix (taking the days of the week into consideration).

To integrate performance over the course of the week into a bid matrix, equally weighted sales have again been included – to show anytime when PPC has catalyzed, attributed to or helped to complete a web order in the purchasing cycle – divided by the number of touch points.

Last click web orders have been added to show when the purchasing cycle was completed, with the last touch point deriving from PPC.

Below you can see the days of the week between July 1st and November 17th 2013 broken down and illustrated in a graph depicting the web orders driven versus the cost incurred. Average CPW increases from left to right, and the days of the week have been ordered in this way. 

Conclusions drawn from performance over the course of the week include:

  1. Tuesday and Friday were comparatively the best performing days of the week for the Example account (both in helping web orders, and last click web orders, and in CPW).
  2. On Thursday and Monday more touch points from other marketing channels come into play and a gap opened between last click and equally weighted web orders (and also in CPW).
  3. All days of the week bar Tuesday will need to be pulled back in terms of bid management as they are either close to or over the benchmark £100 CPW.
  4. Wednesday and Saturday were statistically the worst performing days of the week for the example account, by a considerable margin, both in helping web orders and last click web orders, and in their high CPW (nearly doubling Tuesday’s average CPW, which was the best performing day of the week). 

After analysing the performance over the course of the week, the conclusions from the graph above give the ad scheduling bids in the table below:

 

(please note: bid adjustments can be set from -90% to +900%)

The finished bid matrix

From both the time of day and day of the week analysis, the below bid matrix can be implemented: