MIMIC PRO SIMULATION REPORT
INNOVATION
MIMIC PRO SIMULATION TO UNDERSTAND REAL WORLD DIGITAL MARKETING
Introduction:
In this mimic pro simulation we have to complete 10 rounds based on digital marketing practices. After completing this simulation we will be able to effectively utilize digital tools and make our campaigns successful.
Round 1:
In the first round of this simulation we were given the opportunity to maximize customer return results through A/B testing. After choosing from different option available we ran the test and got moderate results for first round. Many choices were made in this round and some of the choices that were made included choosing the right background from grey and white options, choosing the right resolution size of the picture from available sizes and choosing the right font sizes etc. Historically the average return rate for BUHI was 45% but we were able to get 41%.
Round 2:
In the second round we were asked to increase the conversions through A/B testing. Again like previous rounds various choices were given. The choices that were made were similar to previous round like selecting the right font for web page, selecting attractive web design giving maximum results etc. Once we made a choice we checked it after running the A/B testing whether it is giving the required results or not. After applying the relevant changes we were able to get decent results. 2975 conversions were made with over 41% customer return rate.
Round 3:
In third round the aim was to maximize the product size results. Results show that ideal product size in those circumstances is 3. However we were able to increase it to two products per transaction with our strategy. Some of the choices that were made included the right social media platforms from various platforms available like Facebook, Instagram and twitter etc. We choose Facebook considering the large number of user this platform has.
Round 4:
In round 4 we were asked to maximize the clicks on homepage results. The ideal results were 19000+ clicks. Some of the choices that were made to increase clicks were by adding headlines that attracted more customers and using social media platforms. Moreover special focus was given on bidding prices. By making the right choices were able to generate 20000+ clicks and got excellent results.
Round 5:
In round 5 we were asked to allocate budget to the campaign by selecting various ads and allocating a budget to each. In this round I was not able to get the ideal results as the budget allocated to some campaigns was higher than the suggested budget. Some of the choices that I made were allocating few campaigns a higher budget. The option was available to spend budget on 15 campaigns while I just spend the entire budget on top 5 or 6 campaigns and spent extra amount. Decisions were also made on the basis of CPC. The campaign having highest CPC was Display / Retargeting / Yellow backpack and Display / Retargeting / Satchel had the lowest. 33800 clicks were considered to be ideal and I achieved 27441 clicks.
Round 6:
In round 6 we were provided by an excel sheet and asked some analysis questions regarding the campaign. Questions were about campaign that got highest conversions, which campaign got lowest conversion and conversions rates etc. A new thing was to calculate Cost per acquisition. Display / Google / Purse had the highest cost per acquisition and Display / Retargeting / Satchel had the lowest. Decision was made on the basis of this CPA. I was able to answer the questions correctly and got 10 out 10.
Round 7:
In round 7 the focus was to optimize revenue. Again an excel sheet was provided and various results of each product was provided. I was able to choose the best products from campaign and allocated the recommended budget. Average Revenue per Conversion was calculated by using a formula on the historical data. After this formula those campaigns were selected having the highest average revenue per conversion. For instance, the campaign having highest Average Revenue per Conversions was Paid search / Google / Pouch so it was kept on top. The results were quite good as we generated $146253 revenue from this campaign.
Round 8:
In round 8 we asked to focus on profits. In this round we were provided with a new excel sheet and asked to answer some questions. Decisions were made using Return on Investment. It was also calculated using formulae on the historical data. Campaigns with highest Return on Investment were selected. Few options were also given for upgrade and I choose one of them. I was able to 9 out 10 questions correctly. Questions were related to profit of different campaigns, the highest profit and lowest etc.
Round 9:
In round 9 we were asked to optimize the social campaign. Various platforms like Facebook, Twitter and Instagram were included in this campaign. Based on the excel sheet data we made some decisions and allocated the right budget to highest converting items with lowest rate. Choices were again made on the basis of Return on Investment. ROI was also calculated and analyzed after which the campaigns having negative ROI were separated and campaigns having highest ROI were considered in final selection. For instance, Paid social/ Facebook/ Rolling bag was the campaign having lowest ROI so it was separated and not considered for final selection. As a result we were able to get amazing results.
Round 10:
In the final round we were asked to optimize both paid search and social campaigns. In paid search it included search engines like Google and in Social it included Facebook, Twitter etc. From both types we choose the products having highest conversions, low cost and some other characteristics. Final selection was made and the campaigns having highest return on investment rate were finalized. For instance the campaign Paid search / Bing / Yellow backpack has the highest ROI so it was at the top of our list. We also asked 10 questions in round out which 8 questions were answered correctly.
Conclusion:
This simulation was really helpful in understanding A/B testing and other practical digital marketing skills. By allocating budget and getting instant results we are now able to step in professional digital marketing field and test our skills. Additionally, what I learnt from this simulation is that we should test 1 variable in time to understand the results, consider the profits not design and design a strong hypothesis. Finally allocating the optimum budget for each campaign help us grow exponentially.