FSU CTE 3809 - Kims model of the forecasting process

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CTE3809 FINAL EXAM STUDYGUIDE Kims model of the forecasting process CHAPTER 8 CONSUMER RESEARCH Apparel and supply chain purpose provide appealing and desirable prod and satisfy customer needs wants aspirations Forecast begins with consumer Traditional prod development PUSH system Manuf retailer pushes prod to consumer production driven The push system new styles introduced seasonally doesn t sell marked downs Consumers then choose from abundance of products and only participate in the selection of the product Alternative product development PULL system consumers are demanding prod Requires continuous flow of consumer info to shape product consumer driven Demand activated product development Move from the crowd to mass customization for products 1 First wave early 1980s Building info technologies and building infrastructure for a pull system 2 Second wave Time effiencies inventory reduction a quicker response system and reduced cost 3 Third wave mid 1990s Focus on the consumer Order to delivery few months to a few weeks 4 Fourth wave markets of one segmenting down to the individual level Mass customization and Chris Anderson s The long tail Demand activated pd strategy that uses info and manuf tech to efficiently produce goods with max differentiation with low cost production Mass production mass customization Listening to the consumer What creates customer acceptance What are the customers expectations Is the product competitive Does the prod surprise customers with exciting attributes Consumer spending behavior are they Impulse buying Or Routine purchases Lifestyle based shopping are the consumers purchasing custom products or personalized services Consumer research Qualitative researcher listens to consumer talk or observes them in natural settings Vs Quantitative researcher conducts surveys or experiements with a group of consumers a sample to understand the larger group population Focus group research 9 12 participants recruited by market research firms A stimulus is used One or more people may dominate Not designed for consensus Consumer research Asking why and what questions Focus group research or depth interviews Depth interview Projective techniques allow people to reveal themselves in non threatening ways Ask to select a picture that corresponds to their feelings about a prod brand or shopping situation Create collage representing the personality of a brand project deep emotions this way Collaborative filtering on the web person makes selections Software matches persons selections with those of others consumer receives customized recommendations company learns about consumer prefs Consumer anthropology interviews teens in rooms and look in closets to understand invidual tastes install video camera in store and researchers observe in store shopping behavior Relational marketing communicate with consumers through different media ads on TV or in print Mall intercept studies intercept consumers in the mall ask prelim questions study takes several weeks to design negotiate with study site and distrib research materials Style testing studies pretesting styles with consumers Consumers sit in front of computer screen and asked to indicated preferred color styles etc Survey research actual behavior may be different than survey In store testing measure actual behavior not attitude or intention done through showcase and laboratory stores test stores test merch groups panel research ask questions a group of consumers over time to track changes in attitudes and opinions provides directional information consumer segmentation and forecasting consumer generations diversity cross shoppers shop in disct stores to luxury stores style testing pretesting styles w consumers to id winners vs losers early enough in pd cycle to see which to continue and not continue CHAPTER 9 SALES FORECASTING Real time marketing 21st century marketing execs are info gladiators They take incoming info on consumer behavior and competitons actions Updated as sales happen Fashion hits buyers and sellers interact and share info buyers see patterns in preferences Hits innovation enters system and reaches the mass becomes a hit Fashion volatile new products highly seasonal short life cycles makes forecasting more difficult and inaccurate Basic styles expected to sell at full price Fashion items one hit wonders In between items track sales on a daily basis and react on items trending upward Fast fashion design manuf distrib and sell merch at the speed of fashion fads Assortment planning software helps pinpoint which stock keeping units to offer in each store on what date what quantities Manuf use similar tools at wholesale level to make decisions Sales forecast projection of expected demand given a set of environmental conditions specific time and updated quarterly Sales plan managerial strat to meet and exceed the sales forecast Who needs sales forecast marketing sales financial production distribution managers Sales forecast requires internal data on sales volume marketing future plans for marketing and distrib external data on market info and cultural indicators Internal data grouped by Sales volume Sales volume by geographic area time pd sales channel Sales tracking must be accurate for forecast product family individual prod and stock keeping units Sales forecasting methods Time series forecasting OMTS open model time series or FMTS Fixed model time series Open model time series analysis the time series to determine the components then build unique models and forecast the time series into the future Fixed model time series idea that the forecast for next months sales is the avg of all past sales adjusts quickly to the changing sales conditions Chaos theory patterns do not repeat exactly Correlation or regression tech stat techniques for comparing how a chnag ein one variable causes a change in another ex ad efforts can effect sales volume Provides broad environmental perspective for forecasting sales Qualitative techniques tap into expertise of people Fine tune quantitative foreacasts forecast new prod forecast long range Ways to tap into the expertise of people in house expert exec committee polling experts polling firms execs Delphi method polling experts Ex figuring out sales forecasting Problem skiwear Demand is hard to predict volatile seasonal market prods are new need to book prod early Solution blen expert in house judgements expertise from retail customers and sales data Leading indicators set of eco


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FSU CTE 3809 - Kims model of the forecasting process

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