The MMM begins by gathering data about product sales and related metrics such as income levels and advertisement expenditure during this period. This information should then be plotted onto a graph with sales on one axis and the other variables (income levels, advertisement expenditure etc.) on another axis. If there are multiple products being analyzed together, each product line can then be graphed individually so that it can easily be compared against others.
Next, regression analysis will need to be conducted using software such as SPSS or Excel to measure the relationships between different variables. Regression lines can then be drawn through these points to estimate how much each variable contributes to overall sales changes during the period in question. For example – if we observe an increase in income levels accompanied by an increase in ad spend but no change in price or distribution channels – we would expect positive coefficients for both income levels and advertisement expenditure which would suggest they have both contributed positively to increasing sales during this period.
Finally, once all relevant variables have been accounted for, residual analysis should also be performed which allows us to measure any unaccounted-for effects on sales such as unforeseen events or special promotions that may not have been captured by our initial models. This step helps us further refine our results so that we can better understand exactly how much impact each factor had on overall product sales increases during this period – allowing us determine specifically how effective our marketing efforts were at driving growth for our products over time.
2. What are some potential strategies you might recommend?
Once understanding has been gained into how advertising impacts product sale increases, strategies may then need to be developed based upon what has been learned from market mix modeling findings and residual analyses previously mentioned above.. Depending upon whether ad expenditures are currently reaching optimal return-on-investment goals planned out before beginning campaigns – possible strategies include:
• Increasing/decreasing ad spending depending upon current performance when budget allows – adjusting budgeting allocations between digital media vs traditional media platforms (television commercials vs online ads) depending upon relative effectiveness discovered through MMM results
• Conducting targeted customer segments or personalization campaigns – taking advantage of customer behavior trends uncovered through analytics research processes
• Allocating increased resources towards testing new creative ideas or targeting methods identified through current campaign performance tracking
• Utilizing existing customer loyalty programs & leveraging influencer marketing initiatives where applicable
Longer term strategies could also involve exploring new markets – either domestically or internationally depending upon preferences – utilizing promoted placement opportunities available within select retail stores when feasible along with developing comprehensive analytics dashboards monitoring key metrics across social media channels/website traffic etc….Ultimately however – whatever techniques used must focus ensuring objectives outlined going into scheme remain achievable despite environmental conditions changing around products over timeso that companies truly make best use out their available resources without wasting money unnecessarily
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