MT359 · Unit 9

MT359 Unit 9 evaluation plan example

Integrated Marketing Communications Purdue University Global Free custom sample in 24 to 48h

Before Advent and again after Easter, [400] adults in the Pittsburgh market will be shown a photograph of five freezer-case bags and asked which they recognize. That photograph test anchors the MT359 Unit 9 evaluation plan for Kolbe Street, which gives every communication tool its own measure and ties each to a rung of the Lavidge and Steiner hierarchy.

What this page holds

Every tool gets its own yardstick, from a pack-photo recognition test to publicity pull-through; for MT359 Unit 9, the evaluation plan arranges those yardsticks on the Lavidge and Steiner hierarchy. Searches like "mt 359 unit 9 assignment example", "mt359 unit 9 sample" and "mt359 unit 9 example" land here.

What a finished MT359 Unit 9 evaluation plan looks like

Five pages built on one measurement grid. Rows are the hierarchy's rungs, awareness, knowledge, liking, preference, conviction and purchase; columns are the tools. Advertising is judged by recognition of the red bag from a photograph, targeted to rise from [31] to [45] percent, and by association of pinched by hand with the brand, [12] to [25] percent. Preference is asked at a stated [$1.50] premium, [18] to [26] percent. Publicity is judged by pull-through, the share of placements using the brand's phrase. The promotion is read from shopper-card data against a baseline, the sales calls by new store listings, and the direct list by coupon-code response. Survey waves fall in early November 2026 and early April 2027. Sales appear last, labeled context.

How a MT359 Unit 9 example is structured

Objectives come first, restated as the plan will test them, with a starting figure, a target and a date for each. The grid follows, and its logic is that no tool is asked to prove something it cannot move: publicity is not judged on sales, nor the sales calls on awareness. The survey design comes next, with the same questions asked in both waves and a margin stated for each change. With [400] interviews per wave, the recognition target's 14-point rise clears a margin of 6.7 points and the preference target's 8 points clears 5.7. Behavioral measures from shopper-card data then cover what surveys cannot: household penetration and twelve-week repeat. Sales get a brief section explaining why they are reported but not graded, since a competitor's price cut or a snowstorm moves them too. The plan ends on a reporting calendar.

Six rungs, five tools

The grid pairs each tool with the rung it can reasonably move. Advertising owns awareness and knowledge, publicity supports knowledge and liking, the promotion owns purchase timing, and the sales calls own distribution.

A photograph instead of a question

Recall questions would test the wrong skill for a shelf-bought product. Respondents see five bags as they appear in a freezer case and pick the ones they know, mirroring the recognition task the message analysis set.

Margins stated before the waves

At [400] interviews a wave, a change must exceed about 6.7 points to read as real for recognition and 5.3 for association. Each target was chosen to clear its margin, a point the plan makes openly in a footnote.

Shopper cards for what surveys miss

Household penetration and repeat within twelve weeks come from the grocery chain's loyalty data. They show whether recognition became buying, which a survey answer about intention cannot confirm.

Sales, labeled context

Case shipments and scanned sales are reported every month but carry no target. The plan lists what else moves them, including competitor pricing, weather and the date of Lent, which shifts by several weeks from year to year.

Where marks go in MT359 Unit 9

Measures that do not match the objectives they claim to judge are the most common weakness in MT359 evaluation plans, and metrics listed without targets read as reporting rather than evaluation. Giving each communication tool its own measure lifts a plan, since the course assigns every tool its own work and judges it on that work. Starting figures, targets and dates for every objective are widely expected. Plans that grade the campaign on sales alone usually lose marks, as do plans that ignore sales entirely rather than labeling them as context. Survey designs stating a margin for each change, and choosing targets that exceed it, show a statistical awareness that rubrics in this course often reward. A hierarchy model named and then applied row by row earns more than one merely cited.

Get a MT359 Unit 9 example written to your instructions

Copy the objectives your campaign set and list the tools it uses; the Unit 9 assignment sheet and its rubric finish the request. Due within 24-48h, an evaluation plan, free as a first sample, gives each tool its own measure and deadline, states a margin for every survey change, and reports sales as context rather than as the verdict.

MT359 Unit 9 questions, answered

What is the Lavidge and Steiner hierarchy?

A 1961 model describing the steps a buyer moves through on the way to purchase: awareness, knowledge, liking, preference, conviction and purchase. It is one of several hierarchy-of-effects models used to set communication objectives. In an evaluation plan it helps assign each measure to a stage, so the plan shows which tools are expected to move which steps.

How large does the survey sample need to be?

Large enough that the change you are targeting exceeds the margin of error on the difference between waves. For two waves of [400], that margin runs roughly five to seven points depending on the percentages involved. When a target is smaller than its margin, the honest options are a bigger sample, a longer flight, or a different measure that moves more readily.

Should shopper-card or scanner data be included in a course plan?

Where the scenario allows, yes, since behavioral data show whether awareness turned into buying. Course papers rarely have real loyalty data, so describe what would be requested, from whom and at what cost, and label any figures as assumptions. Pairing one survey measure with one behavioral measure for the same objective is a strong design in most sections.