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Identify offline sales opportunities

Identfiy sales and campaign opportunities at local retail stores  based on online search information.

KEy FACTS

Customer: Insurance Company

Challenge: Different demand for insurances based on location and season

Objective: Identify actionable sales recommendations for regional POS campaigns

Solution: Mash up geo-coded data from online searches with internal sales data to simulate imbalances in demand and supply, and simulate revenue upsides for local agencies

What were the key challenges?

 

With offer 1.000 agencies in Germany and a wide range of insurance products, the alignement of offline sales campaigns with market demand is tricky.

Typical questions were: 

– When is the right time to start which offline POS sales campaign?

– Which product should be included in which sales campaign?

– Which insurance shows high demand in a local market?

– Which insurance promises the largest local sale potential?

– Which agencies need to be trained for which type of insurance?

 

 

How does our solution differ?

 

Within the app, we combine vast amounts of online search information with sales data of the agencies. As both data sources are geocoded, we can detect imbalances between local demand and supply and derive recommendations.

By allowing marketing teams and sales steering team to explore demand and supply over time, marketing campaigns can be timed adequately. Also, local agencies owner receive quantify information, which insurance promises the biggest upside.

On a strategic level, senior insurance executive can explore in which geographic areas new agencies should with be developed. Also given, that certain insurances, require certain know-how, local training and qualification strategies can be rolled out.

“MIGO taps into new online data sources and allows to finetune campaigns, but also sales recommendations to local agencies”

Steffen Schording

Former Director Multichannel Sales, Gothaer Versicherung

View this short 3 minute video to understand our solution

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