Download - How to make big bucks from search trend data
How to make big bucks from search trend datawww.pi-datametrics.com
FORECASTING CONSUMER DEMAND / SEARCH TRENDS 2
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How to make big bucks from search trend dataWhatever your industry, search trend data can enable you to dictate strategy and improve the cost efficiency of your digital efforts.
We’ve taken Google Trend reports to the next level by factoring in competitive data, to help you formulate a new type of content strategy that is commercially valuable.
Google Trend reports give you demand data. We apply another layer. By overlaying our own, proprietary intelligence, we’ve created a search trend report which will show you how to plan and optimize your content for organic ecommerce and bricks & mortar trading. This empowers you to:
• Inform strategy: Identify which products and services consumers are actively searching for.
• Dictate tactics: Build a content strategy for publishing, planning and promoting, based on actual trend peaks and declines.
• Enable accurate forecasting and planning: Plan for YOY trends and know when to trigger or deactivate paid campaigns to improve cost efficiencies.
When a new trend surfaces, consumers act fast.
Digital teams, therefore, need to be as responsive to search trend behaviour and consumer taste as possible, to capitalize on demand.
N.B. We have used our proprietary Organic Value Score and Gamma reports to assign commercial value to trend data throughout this report.Gamma Report
BLACK FRIDAY / RETAIL REPORT 3FORECASTING CONSUMER DEMAND / SEARCH TRENDS
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The six main types of search trendsPredict sales growth and decline with search trend data:
Steady growth over the past few years.*E.g. 2016 saw the growth of ‘Ripped jeans’.
GROWTH
Steady decline over the past few years.*E.g. 2016 saw the decline of ‘Drop-crotch trousers’.
DECLINE
Sudden growth within the past months. Likely to be fleeting.*E.g. 2016 saw the rise of the ‘Off-the-shoulder look’.
SHARP PEAK
Peaked already and starting to decline.*E.g. 2016 saw the fall of ‘Lace up tops’.
SHARP DECLINE
Consistently searched year-round.*E.g. The continuous demand for overall search themes like ‘Coats, jackets & blazers’.
EVERGREEN
Repeats at the same time YOY.*E.g. The significant, one-time peak for ‘Christmas jumpers’.
SEASONAL
*Think with Google Fashion Trends 2016
Forecasted trends Reactive trends
FORECASTING CONSUMER DEMAND / SEARCH TRENDS 4
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Forecasted trends Example: fashion industry Evergreen and seasonal trends are some of the easiest to forecast, as they’re almost guaranteed to occur year-on-year.
We’ve analysed thousands of womenswear terms across eight major themes between October 2015 - September 2016.
EVERGREEN SEASONAL
BLACK FRIDAY / RETAIL REPORT 5FORECASTING CONSUMER DEMAND / SEARCH TRENDS
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All of the search themes displayed in this chart are evergreen trends, as demand will always exist for these categories, yet there is still significant seasonal flux.
We have trended the overall Organic Value of each search theme throughout the duration of the year to:
• Reveal when each search theme peaks and declines in demand.• Highlight which themes present the most commercial opportunity online.
*N.B. We have excluded the theme ‘Dresses’ in this example, as its maximum Organic Value reached over 1.5 million - it, therefore, entirely eclipsed all other search themes.
Trended womenswear search themes Measured against Pi Datametrics Organic Value ScoreRange: Oct 2015 - Sep 2016
Source: Pi Datametrics Gamma report
Coats, jackets & blazersPlaysuits & jumpsuitsLingerie
Skirts & shortsSwim & beachwear
Tops, shirts & knitwearTrousers, jeans & bottomsWedding
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43 Womenswear search themes: Interesting takeaways
‘Lingerie’ is the 2nd most Organically Valuable search theme and peaks highest in December.*
‘Swim & beachwear’ is the 3rd most Organically Valuable search theme and peaks highest in July.
‘Coats, jackets & blazers’ is the 4th most Organically Valuable search theme and peaks highest in November.
‘Wedding’ is the 5th most Organically Valuable search theme and peaks highest in January.
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Data range
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